Chet Kapoor

We just finished our third season of the <a href="http://www.inspiredexecution.com">Inspired Execution</a> podcast! I&rsquo;ve had the privilege of speaking with phenomenal leaders from some of the world&rsquo;s most recognized brands, including Google, Adobe, Asana, US Bank, and many more. They shared the experiences that have shaped them, their proudest and hardest moments, and the lessons they&rsquo;ve learned along the way.
Each episode had a theme based on what we at DataStax call Inspired Leadership. These are a set of principles that I&rsquo;ve developed over the last 20+ years and are deeply personal to me. I loved hearing everyone&rsquo;s unique experiences, perspectives, and advice.
Listen to the <a href="https://www.datastax.com/resources/podcast/season-3-recap">Season 3 recap episode</a> and read below for our greatest moments from this season. I hope you find these insights inspiring and use them to create your own playbook for success.&nbsp;
<ul>
<li style="font-weight: 400;" aria-level="1">Innovate and simplify everything: <a href="https://www.datastax.com/resources/podcast/asana-cpo-human-centered-design-disruptive-innovation">Asana CPO Alex Hood</a> shared how he uses human-centered design as a product methodology. Not only does this create empathy for customer problems, but it also helps with simplicity. Alex also touched on the importance of clarification and repetition. It may seem boring to communicate the same things again and again, but this is crucial for helping people understand how their work is connected to the larger mission.</li>
<li style="font-weight: 400;" aria-level="1">Create a data culture: <a href="https://www.datastax.com/resources/podcast/persistent-empowering-entrepreneurs-and-using-data-for-decision-making">Persistent&rsquo;s Founder Anand Deshpande and CEO Sandeep Kalra</a> talked about the phases of digital transformation. Phase one was about providing a better experience to stakeholders. Phase two is about helping stakeholders make better decisions. Decision-making &ndash; at all levels &ndash; should be data-driven. And Anand brought up an excellent point: To get the most value out of your data, you have to ask the question &ldquo;What do I want to do next?&rdquo;</li>
<li style="font-weight: 400;" aria-level="1">Be an owner: <a href="https://www.datastax.com/resources/podcast/adobe-cto-cpo-building-relationships-enabling-creativity-moving-to-cloud">Abhay Parasnis from Adobe</a> talked about his career journey and how to be an owner. He described his career as a zig-zag and reminded us that no one&rsquo;s path is a straight line. There are twists and turns, and we fumble through some of our decisions. But building relationships along the way is most important. And ultimately, being an owner of the mission you&rsquo;re a part of will be the key to your success.&nbsp;</li>
<li style="font-weight: 400;" aria-level="1">Obsess over customers: When <a href="https://www.datastax.com/resources/podcast/google-cloud-global-director-healthcare-making-customers-product-managers-passion-to-profession">Google Cloud&rsquo;s Aashima Gupta</a> first started in healthcare, she wasn&rsquo;t very comfortable speaking directly to customers. But she practiced A TON. This totally transformed the way she leads teams and builds products. In her words: &ldquo;You have to see the world through the eyes of your customers to truly understand the business problems they are facing and how you can help them.&rdquo;</li>
<li style="font-weight: 400;" aria-level="1">Execute thoughtfully with speed: <a href="https://www.datastax.com/resources/podcast/jim-baum-mastering-execution-weakness-into-superpower">Technology executive Jim Baum</a> started his first business in high school, with a residential tree company called Mr. Tree. Very early on, he understood the importance of execution and why it&rsquo;s key to success. Jim noted that people often confuse activity with execution. If the impact of the activities isn&rsquo;t measurable, you won&rsquo;t get the results needed to be a winning company or leader. It&rsquo;s also important to provide your teams with a framework so they understand what activities are needed in order to execute.</li>
<li style="font-weight: 400;" aria-level="1">Operate at all levels: <a href="https://www.datastax.com/resources/podcast/us-bank-cio-willingness-to-fail-and-power-of-simplicity-scale">Dilip Venkatachari from US Bank</a> talked about what it&rsquo;s like to lead at a small startup versus a large enterprise. When you&rsquo;re leading a startup, it&rsquo;s easy to stay connected to the details. But as you scale, things become more complex. It&rsquo;s all about providing context and auditing frequently. Dilip&rsquo;s advice to coaches is simple: your job is to bring great people together, set them on a path, and stay out of the way while they execute.</li>
<li style="font-weight: 400;" aria-level="1">Diversity and inclusion matter: <a href="https://www.datastax.com/resources/podcast/president-orion-pictures-authentic-storytelling-active-listening-recognizing-unconscious-biases">Orion Pictures President Alana Mayo</a> discussed authentic storytelling in film and how to build teams that represent the world as it is. She shared that creating a diverse and inclusive environment starts with active listening and vulnerability. You have to let go of your ego and allow others to voice their perspectives.</li>
</ul>
Season 3 of IEP was special in many ways - it was short but thoughtful and personal. I&rsquo;ve learned so much and am constantly inspired by these phenomenal leaders. We hope you listen to every episode again and again. Our goal is to provide you with tips and tricks to create YOUR OWN personal playbook for success
We asked all of our guests the advice they&rsquo;d give to a younger version of themselves. Two themes emerged:
<ol>
<li style="font-weight: 400;" aria-level="1">Bet on yourself. Have confidence in your abilities. Don&rsquo;t be afraid to take risks and just go for it</li>
<li style="font-weight: 400;" aria-level="1">Focus on enjoying the journey. Things will happen to you - good and bad. Know that change is inevitable. And finally: you won&rsquo;t remember your bank balance, but you will always remember the people you were in battle with.</li>
</ol>
Thank you for tuning in, and as always, please send any feedback or thoughts to <a href="mailto:inspiredexecution@datastax.com">inspiredexecution@datastax.com</a>. We&rsquo;ll see you for the next season of the Inspired Execution Podcast!

Inspired Execution Season 3: Bet on Yourself and Enjoy the Journey

2021 is coming to a close, and it&rsquo;s been a busy year! Thank you for your continued trust and partnership. Below are a few thoughts from 2021, and a perspective into the year ahead.
DataStax unleashes the data that matters&nbsp;
You&rsquo;ve probably heard me say this before &hellip; all enterprises are on the digital transformation journey. The first phase started with &ldquo;mobile.&rdquo; The second was focused on cloud computing. And today it&rsquo;s all about data - this is the most important phase of digital transformation.
But the requirements for data-driven businesses are evolving. We have to move fast, remove data silos, and solve for fragmentation in order to deliver value. Today&rsquo;s winning enterprises&mdash;who generate revenue with their data&mdash;are doing this with ALL of their data. They have to activate the real-time data that flows in their applications and drives customer experiences. This is the data that runs the business.
Over the last year, we&rsquo;ve combined our NoSQL scale-out leadership with app development and cloud experience to deliver the next-generation, open data stack that is:&nbsp;
<ul>
<li style="font-weight: 400;" aria-level="1">Kubernetes-based for cloud-native agility&nbsp;</li>
<li style="font-weight: 400;" aria-level="1">Developer-ready with APIs to reduce time to market&nbsp;</li>
<li style="font-weight: 400;" aria-level="1">Cloud-delivered to simplify operations and reduce TCO</li>
<li style="font-weight: 400;" aria-level="1">Built around open source technologies, like Apache Cassandra and Apache Pulsar, to support data at rest and data in motion</li>
<li style="font-weight: 400;" aria-level="1">All with global availability and scalability</li>
</ul>
The database of the future&nbsp;
Another HUGE highlight of 2021 was the release of Apache Cassandra 4.0! It is the best release yet, with unmatched quality, scalability, and reliability. We are so grateful to the Cassandra community for all of their work to make this happen.&nbsp;
Everything we see in the market tells us that Cassandra is THE database of the future. NoSQL is growing at a 5-year CAGR of 30%. And everyday experiences like jamming out to your favorite songs on Spotify, binge-watching a new show on Netflix, or calling an Uber to your favorite restaurant are all powered by Cassandra. We are so excited to keep growing the ecosystem around Cassandra while driving innovation.
Supporting your journey to the cloud&nbsp;
We do not think the world needs another database. Rather, the world needs a way to standardize fragmented data environments and a stack that can harness all real-time data, both in motion and at rest. We&rsquo;ve invested in lots of awesome product innovations so we can meet you at any stage of your journey to the cloud.
<ul>
<li style="font-weight: 400;" aria-level="1">Astra DB: The first Cassandra Database-as-a-Service of its kind. You can run it on any public cloud and it has multi-region capabilities. Astra is helping enterprises bend the TCO curve by reducing data costs. It&rsquo;s giving developers freedom of choice and ease of development with APIs and Stargate.&nbsp;&nbsp;</li>
<li style="font-weight: 400;" aria-level="1">Streaming: We delivered a streaming product powered by Apache Pulsar with the acquisition of Kesque and the launch of Astra Streaming. A recent study by GigaOm shows that Pulsar has up to 81% cost savings compared to Kafka and 35% higher performance.</li>
<li style="font-weight: 400;" aria-level="1">Stargate: We added GraphQL and gRPC APIs to help with developer agility.&nbsp;</li>
<li style="font-weight: 400;" aria-level="1">K8ssandra: Our open source distribution of Apache Cassandra on Kubernetes. It now runs on Amazon, Google, Azure, and is available on the VMware Marketplace.</li>
<li style="font-weight: 400;" aria-level="1">Luna DB: Open source Cassandra support to customers that would like to continue self-managing their data.</li>
<li style="font-weight: 400;" aria-level="1">Datastax Enterprise: For customers who need enterprise functionality and support for their mission-critical infrastructure beyond just using Cassandra.</li>
</ul>
Looking ahead
Our goals for 2022 remain the same: partner with you to unlock the data that runs your business. We will continue to deliver products that developers love and that change the trajectory of the enterprises they work for.

2021: A Year of Momentum, Innovation, and DATA

Christophe Bornet

Yesterday's data architecture can't meet today's business requirements for speed, flexibility, and growth. To harness the power of their data, enterprises are turning to modern streaming platforms, like the cloud-native, horizontally scalable <a href="https://pulsar.apache.org/">Apache Pulsar</a>. Yet many still rely on traditional message brokers like RabbitMQ, a once-popular open-source message queueing platform that is struggling to keep up with the scale and performance requirements of today&rsquo;s technology solutions. RabbitMQ suffers from many of the same shortcomings as other legacy messaging platforms - a monolithic architecture that presents serious obstacles to scale and inherent brittleness. As a result, many organizations are seeking an alternative that allows them to continue to leverage their existing investment in RabbitMQ, but without the foundational shortcomings in that platform.
That&rsquo;s why DataStax is pleased to announce <a href="https://www.datastax.com/starlight/rabbitmq">Starlight for RabbitMQ</a>, an open-source, fast-messaging compatibility layer for Pulsar. This solution provides wire-level compatibility with the RabbitMQ API and enables enterprises to take advantage of Pulsar&rsquo;s incredible performance and horizontal scalability without requiring them to rewrite their RabbitMQ applications.
<h2>Starlight for RabbitMQ streamlines enterprise operations</h2>
By combining the industry-standard AMQP 0.9.1 (RabbitMQ) API with Pulsar, this new API provides a powerful way to modernize your RabbitMQ infrastructure while improving performance and reducing costs.&nbsp;
Here are a few key benefits of Starlight for RabbitMQ:&nbsp;
<ul>
<li>Blazing fast RabbitMQ performance Starlight for RabbitMQ scales horizontally up or down without any operational hassles.&nbsp;</li>
</ul>
<ul>
<li>Drop-in replacement for existing RabbitMQ applications Starlight for RabbitMQ provides a drop-in replacement to enable existing RabbitMQ applications to run on Pulsar. It supports commonly used features of RabbitMQ via compatibility with its network protocol, AMQP 0.9.1.</li>
</ul>
<ul>
<li>Message retention and replay Pulsar supports offloading old messages to object storage for practically infinite storage capacity. Applications using Starlight for RabbitMQ can revert to or play previously consumed messages for auditing, testing, and failure recovery purposes. Older messages that are read less frequently can be moved to lower-cost storage like HDFS or AWS S3.</li>
</ul>
<ul>
<li>No message loss Pulsar durably persists messages to disk before accepting them. Once a message is accepted it is guaranteed to be delivered.&nbsp;</li>
</ul>
<ul>
<li>Geo-replication for low latency and disaster recovery Pulsar is designed for asynchronous replication across multiple, geographically separate regions. This enables lower latency because clients are writing to and reading from brokers in their local region, and traffic can be rerouted to surviving regions in the event of an outage.</li>
</ul>
<ul>
<li>Open source to avoid lock-in Starlight for RabbitMQ is 100% open source. You can run it on-premises or in any cloud provider, in Kubernetes.</li>
</ul>
<ul>
<li>Future-proof with a reduced total cost of ownership: Pulsar supports traditional RabbitMQ messaging workloads, but it can also support modern streaming use cases such as log collection, microservices integration, event streaming, and event sourcing. New workloads can run alongside legacy RabbitMQ applications, and because Pulsar is natively multi-tenant, you can do this without the complexity of managing multiple clusters across different lines of business.</li>
</ul>
<ul>
<li>Adds Pulsar functions to RabbitMQ: RabbitMQ provides no native stream processing features; Pulsar functions, on the other hand, enable the creation of complex processing logic on a per-message basis. Starlight for RabbitMQ eliminates the need to deploy additional systems for lightweight computations. Fewer systems or components eliminate the need for ETL processes and reduce time to market</li>
</ul>
<h2>Start streaming with Starlight for RabbitMQ</h2>
Want to start improving your data infrastructure and focus on building new event-driven streaming applications&mdash; all while reducing costs and simplifying operations?
Starlight for RabbitMQ is included in <a href="https://dtsx.io/3DZKSdj">DataStax&rsquo;s Luna Streaming Enterprise</a> support for Apache Pulsar. You can also dig into the <a href="https://dtsx.io/2Z61UYF">Starlight for RabbitMQ source code on GitHub</a> (available under the Apache Software License v2) to learn more about how you can easily leverage the power of Pulsar for your RabbitMQ applications.&nbsp;
Follow <a href="https://dtsx.io/3tRGhWP">DataStax on Medium</a> to keep up with exciting announcements and developer resources on all things Apache, Cassandra, Kubernetes, streaming, and more.&nbsp;
<h2>Other Resources</h2>
<ol>
<li><a href="https://dtsx.io/2Z61UYF">GitHub repo for Starlight for RabbitMQ for Apache Pulsar</a></li>
<li><a href="https://dtsx.io/3DZKSdj">DataStax Luna Streaming</a>&nbsp;</li>
<li><a href="https://pulsar.apache.org/">Apache Pulsar</a></li>
<li><a href="https://www.rabbitmq.com/">RabbitMQ</a></li>
</ol>

Infinite Scale without Fail with Starlight for RabbitMQ 

Bhavani Rao

If you are like most developers, you are embracing applications built using microservices and a NoSQL database. There are many good reasons: faster time to market, lower total cost of ownership, better performance, less downtime, and easy scalability. Creating cloud-native applications is hard because microservices are often written in different languages, database drivers have a maintenance burden, or familiar HTTP APIs lack the performance needed.&nbsp;
We are excited to announce the general availability of a gRPC API for Apache Cassandra. Now you can leverage a powerful database in combination with a microservices-oriented API for performant applications.
Native database drivers offer high performance but not all programming languages have commercially supported drivers. Writing and maintaining a native driver is complex and time-consuming because it involves significant configuration management (retries, load balancing, and pooling, for example). Community drivers alleviate development work but often lack enterprise functionality because active development is intermittent.&nbsp;
Introducing the gRPC API
One way to address these challenges is with gRPC, an open-source, high-performance, remote procedure call (RPC) framework developed by Google. DataStax has leveraged this technology to create a gRPC API to query Cassandra that&rsquo;s 100% open source and already includes client libraries for Go, Rust, Node.js, and Java.
Client libraries send CQL queries from the application to the gRPC API which in turn passes those queries to Cassandra. The gRPC API is part of Stargate, an open-source project that serves as a data API gateway to make it easier to work with data in Cassandra. Stargate sits between your applications and Cassandra and includes schemaless JSON, REST, and GraphQL APIs, providing alternatives to traditional database drivers.
<img src="https://www.datastax.com/sites/default/files/inline-images/gRPC%20blog%20image.png" alt="gRPC blog image" data-entity-type="file" data-entity-uuid="e54091a2-702b-4eea-952b-abf85c67c0c9" />
How a gRPC API can solve your challenges
gRPC is unanimously accepted as the best option for communicating between microservices for two reasons: unmatched performance and multilingual support. Its high-performance results from using a binary data format rather than text-based JSON, resulting in a smaller payload. In some studies this data serialization has made gRPC <a href="https://docs.microsoft.com/en-us/dotnet/architecture/cloud-native/grpc">8X faster</a>. Since gRPC allows for describing a service contract in a binary format, there&rsquo;s a standard way to specify those contracts, regardless of the programming language used, thus ensuring interoperability. If you&rsquo;re creating applications using polyglot microservices, gRPC is the best choice for exchanging data between these services and Cassandra.
Today, DataStax provides a gRPC API with lightweight client libraries for Go, Rust, Node.js, and Java&mdash;with the potential to develop more. If you are creating applications using Go or Rust and struggling because there are no enterprise drivers, these client libraries are a viable option andare far easier to maintain than native drivers. Changes that would normally require a driver update can now be made within the Stargate gRPC API; no client library changes are required. There&rsquo;s no application downtime or recompiling drivers.
By offering a gRPC API, we are lowering the bar for creating clients in existing or new programming languages, enabling you and the Cassandra community to deliver support for languages beyond those directly delivered by DataStax. gRPC autogenerates a non-trivial amount of code used to manage operational tasks such as connection pooling, TLS, authentication, load balancing, retry policies, write coalescing, compression, and health checks. DataStax-maintained message-definition files allow for auto-generation of language-specific code that encodes and decodes protobuffers for communicating with Stargate. Abstracting away operational tasks to the underlying infrastructure is consistent with a cloud-native design pattern.&nbsp;
By creating client libraries for a gRPC API, you avoid developmental tasks associated with creating drivers and operational tasks associated with maintenance and deployment, thus saving time and reducing complexity. If you find yourself working with a language or framework that is early in the adoption cycle, you can use our <a href="https://docs.datastax.com/en/astra/docs/gRPC.html">reference examples</a> to create the needed client library.
In summary, gRPC introduces a potent alternative to native Cassandra drivers&mdash;one that&rsquo;s modern, performant, and microservice-oriented. We recommend using gRPC if you:
<ol>
<li>Need to interconnect microservices written in different languages</li>
<li>Need supported Go or Rust drivers</li>
<li>Need to create a client library for framework/language that doesn&rsquo;t have a driver</li>
<li>Need native driver-level performance without using a driver</li>
</ol>
DataStax will continue to introduce more native drivers and innovate with gRPC to create additional ways to interact with Cassandra.&nbsp;
How to get started
Ready to find out if gRPC is a fit for you? If you are using Apache Cassandra (3.x and higher) or DataStax Enterprise 6.8, download and install <a href="https://downloads.datastax.com/#stargate">Stargate</a>&nbsp;to access the gRPC API. The fastest and easiest way to try out this API is with the free tier on our DBaaS offering, <a href="http://astra.datastax.com">DataStax Astra DB</a>, which already comes out of the box with API endpoints for gRPC. Sign up for a free account today!

Available Now - gRPC for Apache CassandraTM

Swetha Polamreddy

Apache Cassandra&trade;, the open-source, NoSQL distributed database trusted by thousands of enterprises for its unparalleled performance, just got better. Today we are excited to announce a new change data capture (CDC) solution to better connect the real-time data that powers businesses. Cassandra users, including those using DataStax Enterprise, can now capture database changes as a stream of events and expose them via Apache Pulsar&trade; to any downstream systems and clients.
<a href="https://www.datastax.com/cdc-apache-cassandra">DataStax CDC for Cassandra</a> powered by Apache Pulsar enables you to derive substantially more value from your Cassandra data stores. Existing CDC for Cassandra tracks changes at the table level and since the table is usually replicated to multiple nodes in the cluster, it may generate duplicate change events for a single record insert/update/delete. This leads to problems downstream, such as data duplication, conflict resolution, and reconciliation. Whereas DataStax CDC for Cassandra deduplicates changes observed at the Cassandra replica level and exposes a &ldquo;clean&rdquo; set of changed rows (including the entire most recent data in the row) on a Pulsar topic. From there, Pulsar pipes those changes to wherever needed in the enterprise ecosystem.&nbsp;
Pulsar provides a comprehensive platform for building real time data applications, as it can ingest millions of messages with very low latency and process and stream high-volume fast data flows in a distributed environment. Pulsar&rsquo;s multi-layered architecture also enables decoupling of compute and storage, allowing for elastic scalability and support for unbounded message retention on low-cost storage. This feature gives CDC for Cassandra the ability to withstand localized network interruptions for an indeterminate amount of time and resume replication once connectivity is restored. From strengthening data recovery solutions to easily building real-time data pipelines, CDC for Cassandra can be of use in many ways.
Better real-time data pipelines with CDC for Cassandra
Enterprises need to connect data across their organizations to help them make data-driven decisions in real-time or near-real-time and provide the best service to customers and be one step ahead of the competition. Capturing data changes as they happen across different data sources, streaming, processing, and then publishing those changes to a target destination as part of the same system provides a single source of truth. This reduces the surface area for conflicts in security management, schema enforcement, and fault tolerance models.&nbsp;
While Cassandra is a critical part of your data strategy, you also need to ensure that you can easily move data in and out with the ability to integrate with all the other systems and data stores in your organization. Adding CDC for Cassandra allows you to develop real-time data pipelines by leveraging the wide array of connectors and client libraries in Pulsar.
<img src="https://www.datastax.com/sites/default/files/inline-images/CDC%20for%20Cassandra%20blog%20image.png" alt="CDC for Cassandra Blog image" data-align="center" data-entity-type="file" data-entity-uuid="ed519a9d-e976-46d0-9872-87c09a98b4ec" />
Change data Capture for Cassandra in action&nbsp;
Below are some examples of how enterprises can leverage real-time data pipelines enabled by CDC for Cassandra&nbsp;
Enable search integration
Cassandra is a highly scalable database known for its incredible read and write performance. However, sometimes your use case may require moving data from Cassandra into a more purpose-built search solution such as ElasticSearch. In these situations, CDC for Cassandra can simplify this process and automatically update your search indexes in real-time.
Analytics ready data&nbsp;
Traditional business intelligence has long relied on batch processing to move data from operational data stores into data warehouses for reporting and analytical purposes. The lag caused by this batch processing is increasingly at odds with the need for real-time, up-to-the-moment information for business leaders who need to make snap decisions to remain competitive in today&rsquo;s digital world. With CDC for Cassandra, delayed batch jobs can be replaced by immediate updates that automatically stream data changes from Cassandra into your data warehouse solution, providing an accurate picture that always reflects the current state of the data. Enterprises can now both simplify and modernize their data architecture leaving behind the inefficiencies of batch processing.
Operational ML&nbsp;
Data science often involves the analysis of time series data which is not always easy to capture. With CDC for Cassandra, data scientists can more easily access an event stream of time series data that represents the changes that have happened on a table-by-table basis. These time series play a critical role in training ML models which can be used to extract greater insights and predictive capabilities. While these models are valuable on their own, operationalizing them as part of your data in motion strategy can further be achieved by using capabilities such as Pulsar functions to leverage these models to enrich data in real-time as part of your streaming data pipelines.
In today's digitized world, data is the lifeblood of any enterprise and the free flow of data is very critical. As enterprises grow, they tend to add new technologies or services that more often than not lead to multiple systems which are not tied together in a meaningful way. This fragmented architecture is expensive to maintain, difficult to improve, and almost always creates data silos. To resolve this, more and more enterprises are moving towards unified event-driven architectures. DataStax CDC for Cassandra powered by Pulsar is created specifically to help solve these issues. It will help you to simplify, improve and modernize data architectures while eliminating data silos.
Version Compatibility
CDC for Cassandra is compatible with <a href="https://www.datastax.com/products/datastax-enterprise">DataStax Enterprise version</a> 6.8.16 and open source Cassandra, versions 4.0.x and 3.11.x.&nbsp;
Ready to build your own event-driven data architecture?
<a href="https://www.datastax.com/cdc-apache-cassandra">Datastax CDC for Apache Cassandra</a> brings the expertise of DataStax engineers to Cassandra and DataStax Enterprise (DSE) users, in the form of enterprise assistance for enabling CDC use cases. It provides mission-critical support for the following software components:
<ol>
<li><a href="http://downloads.datastax.com/#cassandra-source-connector">DataStax Cassandra Source Connector for Apache Pulsar</a>, a Pulsar IO source connector</li>
<li><a href="http://downloads.datastax.com/#cassandra-change-agent">DataStax Change Agent for Apache Cassandra</a> works with Apache Pulsar, including <a href="https://www.datastax.com/products/luna-streaming">DataStax Luna Streaming</a>. Luna Streaming is professional support from highly skilled DataStax engineers who are experts at operating distributed Apache Pulsar clusters at scale.</li>
</ol>
 <a href="https://www.datastax.com/cdc-apache-cassandra">You can also contact us today to schedule a demo and an architectural discussion.&nbsp;&nbsp;</a>

Shatter Data Silos with DataStax Change Data Capture for Apache Cassandra 

Denise Gosnell 

Join a JavaScript newbie&rsquo;s journey to understanding async and await in this post &mdash;&nbsp;<a href="https://astra-tests.netlify.app/">a live web app</a>&nbsp;that times how long it takes to make asynchronous API calls.
After my first introduction to&nbsp;<a href="https://www.javascript.com/">JavaScript</a>&nbsp;about six months ago, I wanted to reach a deeper understanding of the built-in asynchronous programming concepts within the JavaScript language:&nbsp;<code>async</code>,&nbsp;<code>await</code>, and&nbsp;<code>promises</code>. To teach myself these concepts, I came up with a close to real-world, testable question for this live app:
<div style="color: #eb6c34; border-left: 3px solid grey; padding-left: 20px; font-size: 18px; margin-bottom: 18px;">How long will it take to fetch data via REST APIs from a webpage?</div>
There are many, many ways we can do this.&nbsp;<a href="https://astra-tests.netlify.app/">This post</a>&nbsp;(which is a real, live app) focuses on timing the roundtrip API calls between two different cloud-based services:
<div style="color: #eb6c34; border-left: 3px solid grey; padding-left: 20px; font-size: 18px; margin-bottom: 18px;">1. Webapp hosting and content delivery network (CDN):&nbsp;<a href="https://www.netlify.com/">Netlify</a> 2. Cloud Database:&nbsp;<a href="https://dtsx.io/3lgYQjw">DataStax Astra DB</a></div>
The rest of this post details how I set up the timing tests using asynchronous API calls, and a few hiccups I ran into along the way.&nbsp;<a href="https://dtsx.io/3A0EEsc">Go here for a 10-minute tutorial</a>&nbsp;on how to set up Netlify functions to make API calls to an&nbsp;<a href="https://dtsx.io/3lgYQjw">Astra</a>&nbsp;database.
<h2>How do we set up asynchronous timing tests?</h2>
Let&rsquo;s set up 10 tests. Each test will make 10 asynchronous (in parallel or simultaneous) API calls to our database in&nbsp;<a href="https://dtsx.io/3lgYQjw">Astra DB</a>. Our goal is to time the round trip for each set of asynchronous API calls from a simple web app to our cloud database and back. The pseudocode for this would look like this:
<pre> 1 Write a function to run multiple rounds of tests
 2 For each round of testing
 3 Start a timer in the app
 4 Call a function that will perform asynchronous API calls
 5 Stop the timer in the app
 6 Display the total time for that round</pre>
 The above pseudocode translates into the following JavaScript:
<pre>1 function runTests(rounds, numberAPICalls) {
2 for (round = 0; round &lt; rounds; round++) {
3 var startTime = new Date();
4 timeTest(numberAPICalls).then(() =&gt; {
5 var finishTime = new Date();
6 var timeTaken = finishTime - startTime;
7 );
8 }
9}</pre>
The work of doing the asynchronous API calls is in the&nbsp;<code>timeTest</code>&nbsp;function; we will get to what that does after we take a look at my first mistake.
Click the link below to run this web app&rsquo;s timing suite with the function definition above. Before reading the answer written below the output, can you see what is wrong with the output?
<a href="https://astra-tests.netlify.app/badcalls.html">Run Bad Tests Live</a>
<h2>What&rsquo;s wrong with these results?</h2>
There are two glaring mistakes with the output on the other page that led me to think we weren&rsquo;t setting this up correctly. First, the&nbsp;<code>round</code>&nbsp;number is the same for each series of tests. Second, the&nbsp;<code>startTime</code>&nbsp;is the exact same for each test.
Something isn&rsquo;t right here. It seems like the&nbsp;<code>round</code>&nbsp;number and the&nbsp;<code>startTime</code>&nbsp;are not updating with each subsequent series of tests. Instead, we want both the&nbsp;<code>round</code>&nbsp;number and&nbsp;<code>startTime</code>&nbsp;to wait for the tests to complete before changing the value.
This is where we run into the&nbsp;<code>async</code>&nbsp;and&nbsp;<code>await</code>&nbsp;a pattern in JavaScript.
<h2>What is the <code style="color: #0c153a;">async</code> / <code style="color: #0c153a;">await</code> pattern and how do we use it here?</h2>
Think of&nbsp;<code>async</code>&nbsp;and&nbsp;<code>await</code>&nbsp;as making the code read synchronously (like Python), even though it really isn&rsquo;t.&nbsp;<a href="https://developer.mozilla.org/en-US/docs/Learn/JavaScript/Asynchronous/Async_await">This great blog by Mozilla</a>&nbsp;details the definitions and usages of the&nbsp;<code>async</code>/<code>await</code>&nbsp;pattern. The definition of&nbsp;<code>await</code>&nbsp;is:
<div style="color: #eb6c34; border-left: 3px solid grey; padding-left: 20px; font-size: 18px; margin-bottom: 18px;"><code style="color: #eb6c34;">await</code>&nbsp;can be put in front of any async promise-based function to pause your code on that line until the promise fulfills, then return the resulting value.</div>
We need to pause our code after the test so that the timer can correctly calculate the runtime for each set of asynchronous API calls. Let&rsquo;s change the function above into an&nbsp;<code>async</code>&nbsp;function and tell the code to pause for the entire set of API calls to finish with&nbsp;<code>await</code>&nbsp;before stopping the timer. This changes the function to the following:
<pre>1 <code style="color: #eb6c34;">async</code> function runTests(rounds, numberAPICalls) { 2 for (round = 0; round &lt; rounds; round++) { 3 var startTime = new Date(); 4 <code style="color: #eb6c34;">await</code> timeTest(numberAPICalls).then(() =&gt; { 5 var finishTime = new Date(); 6 var timeTaken = finishTime - startTime; 7 ); 8 } 9 }</pre>
Click the link below to see the results when using the above structure for your testing skeleton:
<a href="https://astra-tests.netlify.app/goodcalls.html">Run Good Tests Live</a>
Great! This testing suite is now properly timing only one round of API calls at a time. Last up, let&rsquo;s take a look at how we are making the API calls.
<h2>How do you kick off a bunch of asynchronous API calls?</h2>
I love how easy it is to use Netlify&rsquo;s&nbsp;<a href="https://www.netlify.com/products/functions/">functions</a>&nbsp;feature. For this project, I created&nbsp;<a href="https://dtsx.io/3z17sPM">one REST API</a>&nbsp;to make calls from Netlify to the database in&nbsp;<a href="https://dtsx.io/3lgYQjw">Astra</a>. In the timing suite, the API call is made in one&nbsp;<code>async</code>&nbsp;function which waits for the payload to return. You can see the same&nbsp;<code>async/await</code>&nbsp;pattern in the function below to make the API call and wait for the result:
<pre>1const addData = async (testNumber) =&gt; {
2 const response = await fetch("/.netlify/functions/writeRestAPI", {
3 method: "POST",
4 body: testNumber,
5 });
6 const responseBody = await response.json();
7};</pre>
The last step in our setup is to make simultaneous calls to this API. We need one last&nbsp;<code>async</code>&nbsp;function for this:
<pre>1 async function timeTest(numTests) {
2 const dataPromises = [];
3 for (let i = 0, ilen = numTests; i &lt; ilen; i++) {
4 dataPromises.push(addData(i));
5 }
6 return await Promise.all(dataPromises);
7}</pre>
I bolded two sections in the above code snippet. First, let&rsquo;s look at&nbsp;<code>Promise.all()</code>. This is the final piece of key functionality for our testing. The use of&nbsp;<code>Promise.all()</code>&nbsp;here will wait for all asynchronous API calls to return before returning the results.
You can find all of the code for&nbsp;<a href="https://dtsx.io/3zVn0WG">this project here.</a>
Follow the&nbsp;<a href="https://dtsx.io/3C3u98d">DataStax Tech Blog</a>&nbsp;for more developer stories. Check out our&nbsp;<a href="https://dtsx.io/3hjcH7G">YouTube</a>&nbsp;channel for tutorials and here for DataStax Developers on&nbsp;<a href="https://dtsx.io/3lcnxgF">Twitter</a>&nbsp;for the latest news about our developer community.
Resources
<ol>
<li><a href="https://www.javascript.com/">JavaScript</a></li>
<li><a href="https://www.netlify.com/">Netlify</a></li>
<li><a href="https://dtsx.io/3lgYQjw">DataStax Astra DB</a></li>
<li><a href="https://github.com/DataStax-Examples/todo-astra-jamstack-netlify#prerequisites">Github Repository: Todo list JAMStack app example with ReactJS + DataStax Astra DB</a></li>
<li><a href="https://developer.mozilla.org/en-US/docs/Learn/JavaScript/Asynchronous/Async_await">Making asynchronous programming easier with async and await</a></li>
<li><a href="https://www.netlify.com/products/functions/">Netlify Functions</a></li>
<li><a href="https://dtsx.io/3z17sPM">Github Repository: Creating a REST API to make calls from Netlify to Astra DB</a></li>
<li><a href="https://dtsx.io/3zVn0WG">Github Repository: Testing API speed for Astra DB in a variety of scenarios</a></li>
</ol>

How Fast Is Netlify + DataStax Astra?

Joshua Norrid 

<a href="https://www.datastax.com/cassandra">Apache Cassandra</a>&reg;, the open source, distributed, and leaderless NoSQL database, has proven to be the backend of choice for modern applications. Like Cassandra, containerized microservices are a distributed system. Today, Kubernetes is the container orchestration platform of choice for launching and operating microservices. So now you have two open-source distributed systems working side by side. Running one distributed system is complicated as it is. Running two distributed systems&mdash;one in the application layer and another in the data layer gets particularly tricky. To simplify this complexity, DataStax came up with <a href="https://k8ssandra.io/">K8ssandra</a> (a portmanteau of Kubernetes and Cassandra), an open-source, cloud-native distribution of Cassandra that provides everything you need to automate the deployment and operations of Cassandra on Kubernetes. With K8ssandra, you can use Kubernetes as a single control plane for managing Kubernetes pods and data clusters, greatly reducing the headaches associated with operating two distributed systems.
Due to inertia in moving off legacy systems, and the need to support data sovereignty and regional latency optimization, the world of infrastructure in the near future is going to be a hybrid one. Enterprises will move some workloads to the cloud, but they&rsquo;ll continue to run some of their workloads on premises, and place others at the edge of the network. That&rsquo;s why we&rsquo;re excited to announce that DataStax has certified K8ssandra on the VMware Tanzu Kubernetes Grid.&nbsp;
VMware has been the king of enabling enterprises to run their workloads on virtualized infrastructure on prem, but with Tanzu they&rsquo;re also playing a leading role in helping enterprises sync their applications and data workloads in a hybrid environment&mdash;whether it&rsquo;s on prem, at the edge, and in any public cloud. This is aligned with DataStax&rsquo;s vision of providing enterprises with the freedom to control their own destiny, and not be locked into any particular vendor when it comes to data management.
Running K8ssandra with VMware Tanzu confers major benefits beyond doing it with plain Kubernetes. For example, <a href="https://docs.pivotal.io/vmware-harbor/index.html">VMware Harbor Registry</a> - an enterprise private registry - makes it easy to manage K8ssandra images for deployment to VMware Tanzu with enterprise-grade security and identity management. There&rsquo;s more. Apache Cassandra can be run seamlessly in a hybrid environment that involves multiple on-prem and cloud clusters. Enterprises that run K8ssandra on Tanzu gain the ability to manage Cassandra clusters across clouds from <a href="https://tanzu.vmware.com/mission-control">VMware Tanzu Mission Control</a>, so they can easily manage access, apply security policies, and inspect clusters for security and configuration risks. This reduces operational burden and unleashes developer productivity to amplify the benefits of Cassandra atop Kubernetes.
K8ssandra also bundles another DataStax contributed open-source project called <a href="https://stargate.io/">Stargate</a>, which enables you to expose the Cassandra database to developers as industry-standard APIs such as REST, schemaless JSON, or GraphQL. Now developers don&rsquo;t have to worry about learning any database query language; they can use the languages and APIs they are already familiar with, and get a jump-start on productivity.&nbsp;
So now we have a simplified way of running microservices on a powerful data backend with less operational headache using a widely popular Kubernetes distribution. We also increase developer productivity by exposing the data backend as modern APIs, and give businesspeople the freedom of choice for running their modern workloads on any cloud.&nbsp;
To learn more about the advantages of running K8ssandra on VMware Tanzu, check out this <a href="https://www.datastax.com/resources/datasheet/k8ssandra-vmware-tanzu">whitepaper</a>. Read more about <a href="https://tanzu.vmware.com/tanzu/">VMware Tanzu</a>, <a href="http://k8ssandra.io">K8ssandra</a>, and what DataStax has done to make it easy to <a href="https://www.datastax.com/partners/vmware">run Cassandra on VMware</a>.

Run K8ssandra on VMware Tanzu and Cut Hybrid Database’s Operational Complexity by Half

Wens Gerdyman

 Sundar Balasubramanian

The brave new world created by cloud, IoT and mobile devices, and always-available customer engagements has presented enterprises with many opportunities to innovate, expand their business, and get closer to customers. In order to improve application performance and increase business agility, <a href="https://www.datastax.com/enterprise-success">many enterprises have decided to move modern workloads</a> from relational databases to NoSQL ones like Apache Cassandra®. Unlike relational databases, Cassandra is world renowned for its linear scalability, always-on availability, and blisteringly fast write-read performance that enterprises have found a good fit for modern workloads. (Learn more about the <a href="https://www.datastax.com/resources/whitepaper/data-modernization-a-future-state">future state of data modernization</a>).

As with any transformation projects, migrating workloads from RDBMS to Cassandra is not straightforward. Many enterprises are stuck because there is a dearth of tools, skilled resources, and partners who can help with migrations, modernization strategy, and execution. To alleviate this problem, DataStax has developed the RDBMS-to-Apache Cassandra accelerator, a comprehensive set of tools that enable enterprises to assess, plan, and design the migration of RDBMS workloads to Cassandra.

The accelerator provides a quick and easy way to probe the source relational database, assess the relational tables, relations, query patterns, and stored procedures of the workloads that enterprises want to migrate. These assets, once discovered, make an excellent starting point for planning the microservices that should be developed in the applications. The assessment and planning tools of the accelerator are accessible from a single GUI, allowing you to visually explore and analyze the assets. The accelerator also makes the job of developing on Cassandra a little easier. Based on rules that have been formed through more than a decade of experience, the accelerator recommends a target Cassandra data model, which developers can further fine tune.

Here is an overview of the tools available in the accelerator (refer to the blue boxes in the below diagram).

Assessment

<ul>
	<li>Source database Inventory / Metadata / Logs Extractors enable you to extract relational database schema, metadata, query logs, session logs, tables, joins, triggers, stored procedures, etc.</li>
</ul>

Planning &amp; Design

<ul>
	<li>Source Table and Source Query Analyzers enable you to methodically examine the logs, tables, query patterns, frequency of queries, etc.&nbsp;</li>
	<li>Relationship Cluster Builder enables you to view related source tables</li>
	<li>Cassandra Schema Modeler/Recommender enables you to review and edit recommended Cassandra schema, and define and finalize your Cassandra physical schema&nbsp;</li>
	<li>Model Verification utility enables you to validate source vs target data type mismatches, and compare source vs target models and queries.</li>
</ul>

<img alt="Blog Diagram" data-entity-type="file" data-entity-uuid="b6111a1b-f289-4df7-9a63-034591558a8b" src="https://www.datastax.com/sites/default/files/inline-images/Untitled.png" /> 
&nbsp;

Blue box: tools in the new RDBMS-to-Apache Cassandra Accelerator by DataStax

Orange box: core data migration tools by DataStax

Green box: other migration tools typically brought by clients

On the services side, DataStax is offering the <a href="https://www.datastax.com/resources/datasheet/RDBMS-Cassandra-Migration">RDBMS-to-Apache Cassandra Migration Assessment and Strategy Package</a>, built around the accelerator. Taking advantage of the services along with the accelerator and core data migration tools by DataStax can reduce the migration timeframe by as much as two-thirds. You will be well on your way to modernizing your applications and migrating your data seamlessly, and achieving the desired outcomes of better application performance and improved business agility.

 
Learn more about the new <a href="https://www.datastax.com/resources/datasheet/RDBMS-Cassandra-Migration">RDBMS-to-Apache Cassandra Accelerator and its related services package</a>, or <a href="https://www.datastax.com/contact-us?source=services/professional-services#general-inquiries">contact us</a> to schedule a free initial consultation. We will help you develop a comprehensive strategy for migrating your relational monoliths to Cassandra.

Get a move on! New tools from DataStax reduce RDBMS to Apache Cassandra migration time by two-thirds

Alice Lottini

Jeff DiNoto

If you are an enterprise that has been undergoing digital transformation, today you are entering a critical step: data modernization. Whether building new modern applications or moving existing workloads to the cloud, you don&rsquo;t want to leave data behind and continue using legacy databases that compromise performance and business agility.&nbsp; You want to take advantage of a new breed of database-as-a-service that offers your development teams zero operational headaches and the agility to bring new applications faster to market.
If you are wise enough to already be running Apache Cassandra&reg; workloads on prem, you may want to consider DataStax <a href="https://www.datastax.com/products/datastax-astra">Astra DB</a>, a Database-as-a-Service (DbaaS) built around Cassandra that offers many additional benefits. You don&rsquo;t have to worry about operations or maintenance; you can choose which cloud vendor you want to work with without the worry of getting locked in; it autoscales out or in with your demand; and most importantly you pay only for what you use. In fact, according to a GigaOm study, you can <a href="https://www.datastax.com/gigaom-tco">save up to 75% in TCO</a> using Astra DB compared to running Cassandra on your own.
Eliminating operational overhead and saving costs are all great reasons for moving workloads. However, it is a serious undertaking that often gives people pause before making the big step. Many hesitate to pull the trigger because workload migration typically involves some downtime, which is very disruptive to the business. Fear no more. DataStax&rsquo;s Zero Downtime Migration product can help you move any existing Cassandra workloads to Astra DB without any business interruptions.&nbsp;
In fact, while this tool fully addresses the needs of those interested in adopting Astra DB, its flexible design enables it to be deployed outside Astra DB to help workload migration between any Cassandra compatible origin and target clusters, such as:
Cassandra ⇄ Cassandra
Cassandra ⇄ DataStax Enterprise&nbsp;
DataStax Enterprise ⇄ DataStax Enterprise
Now let&rsquo;s explore how it works.
<h2>How it works</h2>
At a high level, we use a proxy that provides dual-write capabilities between two clusters. In the scenario discussed here, a self-managed (origin) cluster and Astra DB (target). The proxy ensures that all write requests are executed against both clusters and that reads are executed against the origin. This way, while in operation, the client application continues to operate as if it&rsquo;s only interacting with the origin cluster. Later in the process, reads can be switched over to the target cluster, so that this becomes the primary source of truth while the origin is still kept up-to-date for easy rollback purposes.
While it functioned in much the same way as this next generation of the tool does, <a href="https://www.datastax.com/blog/four-steps-migrate-live-data-apache-cassandra-astra-zero-downtime">the initial version</a> was too attached to Astra DB. As Astra DB has evolved to better suit the needs of our users, so too has the proxy.&nbsp; We thought long and hard, and changed the deployment model of the proxy so that it can now support migrations to serverless Astra DB as well as other potential use-cases.
Here is a high-level diagram of the proxy deployment reference architecture for migration, highlighting the proxy at the center of the system.
<img src="https://www.datastax.com/sites/default/files/inline-images/pasted%20image%200_8.png" alt="No Downtime blog" data-entity-type="file" data-entity-uuid="169e055c-afb8-46b2-9e22-358e3cdbb566" />
One of the key changes with this generation of the proxy is its ability to be deployed outside of the Astra infrastructure&mdash;closer to the client application. This is important for a few reasons:
<ol>
<li>It makes the proxy more flexible; the proxy can be deployed in multiple types of environments and support different types of migrations.</li>
<li>It puts users in control, as they can make decisions about deployment that are effective and efficient for their application to improve security and performance.</li>
<li>It simplifies and standardizes the interaction with Astra, because the proxy now connects to Astra just like any other application client would, using a Secure Connect Bundle.</li>
</ol>
It&rsquo;s also worth noting that the proxy has been designed as a stateless service that can be scaled horizontally to provide several benefits:
<ol>
<li>High availability - multiple instances of the proxy should be deployed to provide redundancy for a now critical piece of the application infrastructure.</li>
<li>Consistent performance - additional instances of the proxy can be deployed in situations where an increased number of connections must be handled, providing for more consistent performance under heavy load.</li>
</ol>
<h2>Easy deployment</h2>
While a major goal of this generation of the proxy is deployment flexibility, we also want to make the developer and operator experience as positive as possible. To that end, along with the proxy itself, we are also delivering some automation that will help not only with the deployment of the proxy itself, but also the infrastructure and networking used to deploy it within.
Specifically in this release, the following automation tools are made available:
<ul>
<li>Terraform modules for AWS infrastructure deployment</li>
<li>Ansible playbooks for infrastructure-agnostic proxy deployment and configuration</li>
</ul>
We chose Terraform and Ansible because they are best-of-breed tools which are well-known, simple to install, and can be run anywhere.
It&rsquo;s important to note that while we believe this automation can help set the stage for a successful migration experience, it&rsquo;s totally optional, and there&rsquo;s nothing about the proxy implementation that prevents a completely bespoke deployment approach.
The modular design incorporated into the automation tooling allows the operator to pick and choose from the tooling that best suits their environment. For example, if infrastructure and connectivity are already established, the Ansible playbooks can be used on their own to target that existing infrastructure. This can leave the operator in total control of their infrastructure while still getting a turnkey proxy deployment experience. The Ansible playbooks can also be used to change the configuration of the proxy deployment, another key feature that the automation provides.
<h2>Deploy with best practices built-in</h2>
One of the benefits of taking advantage of the automation we&rsquo;ve built is that it creates a best-practices-driven infrastructure environment that can make management easier over time.
The infrastructure automation provided via Terraform lays out a foundation for deployment that includes a number of noteworthy features:
<ul>
<li>Monitoring capabilities - resources are deployed that provide metric collection and dashboarding visualization of the deployed proxy instances.</li>
<li>Network segmentation - resources are deployed into their own VPC that can only be accessed through peering configurations, limiting network access and making the system more secure. Peering is performed automatically, making the experience simple and quick.</li>
<li>Resource isolation - because resources are deployed in an isolated environment, once the migration process is complete those resources can be torn down without a risk to other existing infrastructure.</li>
</ul>
<h2>Conclusion</h2>
The Zero Downtime Migration tool is proof of DataStax&lsquo;s continued investment in making it frictionless for enterprises and users to adopt and upgrade to Astra DB in their quest to become more agile and develop innovative applications with a no-ops modern data platform, while at the same time reducing TCO. The tool is capable of helping you move any Cassandra workloads to Astra DB; indeed, between any Cassandra-compatible source and target.
Consistent with DataStax&rsquo;s open data stack philosophy, we are planning to open source the proxy codebase later this year to make it available to anyone looking to improve their ability to migrate applications between clusters and infrastructure while still delivering a consistent application experience for their users. As the project evolves, we hope that through collaboration with the community we can expand these capabilities and add a needed tool to the belt for operators of C* clusters of many flavors. &nbsp;
For now, get a move on and <a href="https://www.datastax.com/contact-us?source=services/professional-services#general-inquiries">contact us</a> to schedule a free initial consultation about Zero Downtime Migration with our professional services group. We will help you develop a comprehensive strategy and assist with migrating your Cassandra workloads.

Want to move to no ops Astra DB with no downtime? No problem!

Pieter Humphrey

Learn more about Functions-as-service (FaaS), Astra DB, and Node.js on the <a href="https://dtsx.io/399nFrC">upcoming Livestream</a> with Alex Ellis, OpenFaaS, and Stefano Lottini from DataStax!&nbsp;
When: Thursday, September 16th at 4:00 p.m. BST//11:00 a.m. EDT/8:00 a.m. PDT.
To get the most out of the live event, be sure to check out the OpenFaaS <a href="https://dtsx.io/3llZ6xt">blog</a> first!&nbsp;
Did you ever wish you had persistent storage for your serverless functions? Storage that was as easy as an idiomatic API call in your favorite language? What if you could even handle JSON data with no upfront schema definition? Functions as a service (FaaS) are excellent containers for business logic. With functions, you can:&nbsp;
<ul>
<li>Run backend code without managing any infrastructure whatsoever.</li>
<li>Run short-lived code that starts FaaST, runs and shuts down when complete or unused.</li>
<li>Run your code in a specific framework or library of your choice.</li>
<li>Trigger a function based on events that are defined by the FaaS provider.</li>
</ul>
That&rsquo;s great, but what happens to the application state? Yes, you could run an in-process cache, session store, or use the modest filesystem allocated to the function. But these workarounds will be as short-lived as the function, so it&rsquo;s not what most people consider persistent storage.&nbsp;
Using APIs and or Drivers, you can get data out from your functions and into a database, but not many databases employ <a href="https://www.infoq.com/articles/serverless-data-api/">data API gateways</a> or offer easy ways to surface a fluent data access layer in APIs like REST or GraphQL. Perhaps you have JSON data and you simply want a document-style NoSQL option that skips defining the schema upfront &ndash; just JSON and go.
So let&rsquo;s assume getting to your database is easy with APIs, drivers, and schemaless JSON for a moment. Why then, would a serverless, autoscaling database be the preferred choice for persistent storage for your serverless, autoscaling functions? First off, it&rsquo;s important to understand that serverless and FaaS are <a href="https://www.bmc.com/blogs/serverless-faas/">not quite the same thing</a>. The key thing that makes FaaS and Serverless DBaaS so great together is autoscaling.
If you've invested in DBaaS and FaaS, you're probably not interested in managing infrastructure. Running serverless functions that have the potential to autoscale up rapidly is dangerous if connected directly to a back-end database that cannot auto-scale.&nbsp;
Scaling up the application dynamically could put an unpredictable and increasing load on a data service or database that doesn&rsquo;t use a similar (auto) scaling mechanism. The industry spent years trying to solve this problem in the application server era with connection pools and database connection conservation techniques. Most of those techniques are antithetical to FaaST-startup-and-terminate style serverless functions because there&rsquo;s no connection to preserve!
Pairing an autoscaling application tier to a data tier that doesn&rsquo;t autoscale drags down a system that could have otherwise been fully automated. Manually running a terraform script, or worse, waiting for an operations ticket to be created and serviced for scaling the database instance up or down would kill 50% of the automation value between application (function) and database. No Bueno.
So how can we wire together an autoscaling DBaaS like <a href="https://dtsx.io/3huclLu">DataStax Astra DB</a>, with serverless functions without having to write a ton of REST services to expose the database functions you need? Let us show you how!
Join <a href="https://www.linkedin.com/in/alexellisuk/">Alex Ellis</a> and <a href="https://www.linkedin.com/in/stefano-lottini/">Stefano Lottini</a> from DataStax on a Livestream this Thursday, September 16th at 4:00 p.m. BST//11:00 a.m. EDT/8:00 a.m. PDT to learn how to pair FaaS with a serverless, autoscaling DBaaS for end-to-end automated scaling. Alex and Stefano will be ready to take your questions live and cover a number of different use cases!&nbsp;
Subscribe &amp; remind 👇
Join the Livestream:&nbsp;<a href="https://dtsx.io/399nFrC">https://www.youtube.com/watch?v=uJyufpJ3204</a>
Learn More:
<ul>
<li><a href="https://cassandra.apache.org/_/index.html">Apache Cassandra</a></li>
<li><a href="https://stargate.io/">Stargate.io</a></li>
<li><a href="https://www.openfaas.com/">OpenFaaS</a></li>
<li><a href="https://nodejs.org/">Node.js</a></li>
<li><a href="https://dtsx.io/3huclLu">Astra DB</a></li>
<li><a href="https://dtsx.io/396Pzoc">DataStax Developers</a></li>
</ul>
Follow the <a href="https://dtsx.io/3kaOEK1">DataStax Tech Blog</a> for more developer stories. Check out our <a href="https://dtsx.io/3lj04L3">YouTube</a> channel for tutorials and here for DataStax Developers on <a href="https://dtsx.io/3z9Q1wK">Twitter</a> for the latest news about our developer community.

Serverless Storage for Your Node.js Functions with Astra DB

To be competitive, your applications must be highly responsive and available anywhere, anytime. The best way to achieve this is to have a database that is geographically distributed and active-active. Unfortunately, the cost and complexity of standing up replicas of your database in multiple regions has been a significant hurdle for all but the largest enterprises &mdash;until now.
We&rsquo;re excited to announce that <a href="https://www.datastax.com/products/datastax-astra">DataStax Astra DB</a>, the serverless, multi-cloud Database-as-a-Service (DBaaS) built on Apache Cassandra&reg;, now supports multi-region deployments. Astra DB can be deployed in multiple regions on one of three cloud providers (AWS, Azure, and Google). It&rsquo;s serverless and employs a consumption-based pricing model that dramatically reduces the total cost of ownership, putting multi-region databases within your budget. You can easily spin up a database, scale it to multiple regions, all within a few clicks to support your disaster recovery, data sovereignty, and latency needs.
<h3>Ensure business continuity</h3>
Data replication is an important way to support a disaster recovery plan. Outages in cloud provider regions are an inescapable reality; they can lead to major business disruptions. By replicating data across regions you enable business continuity in the event of a disaster by having your app connect with a region that is still up and running.
Many countries have data sovereignty requirements, which mandate that data must reside within a particular geography. Astra DB enables you to specify whether data is replicated within a country, or replicated globally.&nbsp;
With this latest release, Astra DB enables you to take advantage of an active-active architecture. Some distributed databases are active-passive, meaning that there is only one primary node that accepts writes. When a region fails, a new primary node must be chosen, which means you lose transactions. With AstraDB you can write to any region, your applications can continue to serve users in case one of the regions goes down.
<h3>Reduce latency</h3>
Latency is another key issue that multi-region Astra DB helps you solve. If your application and database is in Ireland and your end users are in the western United States, there could be several routers that your data traffic will pass through to reach the database, and this can introduce significant latency. Now you can avoid this problem by replicating the data to an Astra DB region in the western US and place the application in the same region. It&rsquo;s a key way to help you deliver the most responsive customer experience.
<h3>Lower TCO</h3>
We&rsquo;re knocking down one of the most significant barriers to using a multi-region database: cost. Operating any database by duplicating data across multiple regions is expensive because you're paying for fixed infrastructure. Our serverless architecture is a game changer because pricing is consumption-based. Enterprises only pay for the writes they make in these regions to duplicate the data, data transfer charge and disk storage. With serverless Astra DB, multi-region is no longer just the realm of big enterprises with big budgets&mdash;it&rsquo;s within reach of any organization.
We&rsquo;ve also simplified the process for configuring and managing a multi-region, distributed database. The Astra UI console reduces to just a few clicks the laborious process of setting up VMs and networking, installing software, adding users, replicating data, and setting up network policies.&nbsp;
<h3>Ready to add a region?&nbsp;</h3>
Log into&nbsp;<a title="https://www.datastax.com/blog/finally-elastic-pay-you-go-cassandra-database-azure" href="https://www.datastax.com/blog/finally-elastic-pay-you-go-cassandra-database-azure" data-renderer-mark="true">Astra DB</a>, select the database you want to replicate in another region and click the Add Region button as shown in this video. At this time, the Pay As You Go and Enterprise tiers will allow users to use Multi-region functionality.&nbsp;
<iframe title="YouTube video player" src="https://www.youtube.com/embed/2dl7RfVKfFI" width="560" height="315" frameborder="0" allowfullscreen="allowfullscreen"></iframe>
Need more information? Learn more details in our <a href="https://docs.datastax.com/en/astra/docs/db-multi-region.html">documentation</a>.
If you&rsquo;re not using Astra DB, get started without a credit card by registering for an account at <a href="https://astra.datastax.com/register">https://astra.datastax.com/register</a> and use your Google or GitHub account to sign in (you can also sign up using your email address). Sign up to get 30 million reads, 4.5 million writes, and 40GB storage for free monthly ($25 credit). Alternatively, you can use your cloud marketplace credits toward Astra DB use.&nbsp;

Introducing the Only Serverless Database for Multiple Regions and Multiple Clouds

Adoption of DataStax <a href="https://www.datastax.com/products/datastax-astra">Astra DB</a> is accelerating, users love the speed and ease in spinning up Cassandra clusters in minutes rather than weeks. Coupled with autoscaling and consumption-based pricing, Astra DB is a clear choice for enterprises that need high availability and infinite scalability. To help support our security conscious users on this journey,&nbsp;we&rsquo;re excited to announce the&nbsp;general availability of private endpoint on AWS, GCP and Azure.
Private endpoint enables enterprises to safely and easily connect applications or microservices in their virtual private cloud (VPC) to Astra DB. Cloud network configuration can be complex, especially with multi-cloud deployments or when connecting services from multiple SaaS vendors. By providing the ability to define private endpoints with private communications from your cloud infrastructure provider, Astra DB helps meet the security and governance requirements of enterprises.
What are the benefits of private endpoint?
One of the threat vectors associated with connecting services to the cloud is that traffic is exposed to the public internet, even if you&rsquo;re connecting services within the same cloud provider. With private endpoint, all traffic remains within the cloud provider&rsquo;s private network backbone and the VPC need not have an internet gateway. By removing access to an internet gateway, the VPC is insulated from threat vectors lurking in the public internet and is protected from any resources accidentally being launched in the VPC.
Our users are incredibly resourceful and many have used VPC peering as a workaround to connect virtual private clouds without transiting over the public internet. However, this is laborious and complicated. Everytime VPC peering is configured, users have to remove conflicting IP addresses or overlapping <a href="https://en.wikipedia.org/wiki/Classless_Inter-Domain_Routing">Classless Inter-Domain Routing</a> (CIDR)&nbsp;blocks from the networks being connected. This complexity increases as more and more VPCs are peered.&nbsp;
Additionally, when using peered networks, all the services in the VPC are exposed, which may not be the intended approach. Users can associate private endpoint with security groups that can be used to enforce governance on network traffic through security group rules. Private endpoint is scalable and an order of magnitude easier to configure than VPC peering.
One common use case for private endpoint is connecting Astra DB to your cloud provider-hosted resources such as your applications or microservices. You can also use private endpoint to connect Astra DB to third-party vendors that host services such as data analytics, etc. Business units within an enterprise may host their applications on separate virtual private clouds, and private endpoint can connect Astra DB to these applications.
<img src="https://www.datastax.com/sites/default/files/inline-images/pasted%20image%200_5.png" alt="Private Endpoint Astra DB diagram" data-entity-type="file" data-entity-uuid="cadd74c2-7dc3-4a3e-9bf1-a92814d4e4aa" />
How do I get started?
Private endpoint supports AWS PrivateLink, Google Private Service Connect, Azure Private Link and is configured using the&nbsp;Astra DB DevOps API.&nbsp;As with all peering connections, the service needs to be enabled in Astra DB and in the user&rsquo;s VPC. The Astra DB private endpoint appears in the user's VPC, enabling direct connectivity to the database via private IP addresses. Users can then accept the private endpoint and choose which of their VPCs have access to Astra DB. This effectively allows Astra DB to function like a service that is hosted directly on the user&rsquo;s private network.
Unlike traditional VPC peering, connectivity works out of the box, without any additional configurations on routing tables and security groups. We also intend to allow users to configure private endpoint through the Astra UI or console shortly.&nbsp;Private endpoint allows security conscious users to connect to Astra DB; a managed service built on Apache Cassandra &trade; easily and safely.
Ready to configure your private endpoint? See <a href="https://docs.datastax.com/en/astra/docs/private-endpoints.html">our documentation</a> to get started.&nbsp;
If you&rsquo;re not using Astra DB, get started without a credit card by registering for an account at <a href="https://astra.datastax.com/register">https://astra.datastax.com/register</a> and use your Google or GitHub account to sign in (you can also sign up using your email address). Sign up and receive US $300 worth of free usage to create a proof of concept or deploy into production from the same environment.

Private Endpoint Security is Here: Another Step Forward for Astra DB Security

The DataStax Blog

Company

FEATURED · Company

Inspired Execution Season 3: Bet on Yourself and Enjoy the Journey

Company

2021: A Year of Momentum, Innovation, and DATA

Company

Infinite Scale without Fail with Starlight for RabbitMQ

Company

Available Now - gRPC for Apache CassandraTM

Company

Shatter Data Silos with DataStax Change Data Capture for Apache Cassandra

Company

How Fast Is Netlify + DataStax Astra?

Company

Run K8ssandra on VMware Tanzu and Cut Hybrid Database’s Operational Complexity by Half

Company

Get a move on! New tools from DataStax reduce RDBMS to Apache Cassandra migration time by two-thirds

Company

Want to move to no ops Astra DB with no downtime? No problem!

Company

Serverless Storage for Your Node.js Functions with Astra DB

Company

Introducing the Only Serverless Database for Multiple Regions and Multiple Clouds

Company

Private Endpoint Security is Here: Another Step Forward for Astra DB Security

Company

The Fast Lane and the Open Data Stack