April 2021 Summaries

The Serverless Handbook warns about the difficulties with AWS. However, there are now three distinct but compelling APIs for "real AWS Lambda functions" - Amplify's, Netlify's, and Vercel's. These platforms offer developer-friendly wrappers for AWS Lambda deployments, making it easier to get started without needing an AWS account or dashboard. The author compares these three APIs in terms of simplicity, documentation style, dev servers, file structures, and commands to remember. While there are slight differences between the platforms, they all offer great developer experiences with state-of-the-art DX. The author ultimately chooses Vercel due to its integration with Next.js framework but acknowledges that it's a close call and may try other languages and APIs in the future.

The Serverless Handbook warns about the difficulties with AWS. However, there are multiple platforms that provide developer-friendly wrappers for AWS Lambdas deployments, such as Netlify and Vercel. These platforms offer different APIs for "real AWS Lambda functions," each with its own strengths and weaknesses. The author's experience with these platforms has been mostly positive, with fewer gotchas than expected. While the choice between Amplify, Netlify, and Vercel may depend on individual preferences and needs, the author ultimately decided to use Vercel due to its integration with Next.js framework.

DataStax is now offering Luna for Apache Cassandra® (C*) 4.01, providing enterprise-grade support for open source software users and enterprises. The C* community has made significant improvements in the upcoming 4.0 release, including increased throughput, reduced latency, and easier monitoring. Luna is a subscription service offering support from experts who contributed to Cassandra code. It comes in three tiers: Essentials, Professional, and Enterprise, with no node limits and access to the Luna portal for interaction with C* support team. Starting today, C* 4.0 will be supported by Luna, and future plans include extending support to cover running C* 4.0 in Kubernetes with K8ssandra.

DataStax has announced the general availability of its serverless multi-cloud Database as a Service (DBaaS) offering, Astra, built on Apache Cassandra® and now available on Microsoft Azure. The platform aims to provide users with the least friction and expense while leveraging the best capabilities of Cassandra. Astra offers a truly consumption-based model for operations and billing, allowing automatic scaling based on usage and pay-for-what-you-use pricing. It is designed to help enterprises avoid cloud vendor lock-in and support multi-cloud, hybrid solutions. The platform abstracts all operational aspects, enabling developers to focus on app development and delivery. Astra can be accessed via the Azure marketplace or through the familiar Astra portal on DataStax's website.

The seventh installment of the season features a conversation between Chet and Steve Mills, Global CIO at iHeartMedia. Join the mailing list for notifications on new episodes. Sri Shivananda discusses his journey from aspiring pilot to technology leader, fascination with computing, and importance of cross-functional alignment in organizational success. Luis Uguina talks about transforming banking industry, why banks have traditionally approached customers wrongly, and the need for digital transformation initiatives. Hari Moorthy shares how mindfulness and meditation improve his career, link between imagination and innovation, and the significance of listening to oneself. Tune in for more insights from impactful leaders on inspiring their teams.

The seventh installment of the season features a conversation between Chet and Steve Mills, Global CIO at iHeartMedia. Join the mailing list for notifications on new episodes. In recent episodes, Sri Shivananda discussed his journey from aspiring pilot to technology leader, emphasizing the importance of observation and continuous learning. Luis Uguina talked about transforming banking through digital initiatives and following gut instincts in one's career. Hari Moorthy shared insights on using mindfulness and meditation for career improvement and the link between imagination and innovation. Tune in for more inspiring stories from industry leaders.

The Open||Source||Data podcast is a must-listen for those interested in open source technology, architectures, and data. Hosted by DataStax Chief Strategy Officer Sam Ramji, the podcast features conversations with leading thinkers from various fields such as data on Kubernetes, data meshes and fabrics, knowledge graphs, responsible AI, open source in academia, and science and analytics. The podcast aims to spread the knowledge of innovators and foster a community of friends interested in the future of open source data.

The Open||Source||Data podcast focuses on the future of open source technology, architectures, and data. Hosted by DataStax Chief Strategy Officer Sam Ramji, it features conversations with leading thinkers in the field, discussing topics such as data on Kubernetes, knowledge graphs, responsible AI, and science and analytics. The podcast aims to spread knowledge from innovators and foster a community of friends interested in open source data's role in technology's future.

DataStax Astra has released a new version with updates to its user experience, including new pricing plans and simplified database creation process. Users can start for free with the "Pay as you Go" plan, which includes $25 monthly credits for up to 30 million reads, 4.5 million writes, and 40 GB of storage. The latest version also introduces a dashboard displaying usage statistics across all serverless databases, new database details header, and organization management updates. Additionally, the platform now supports IAM-based authentication and authorization with granular access control via application tokens.

Kirill Merkushev, Head of Backend at Vivy, a digital healthcare platform, shares his company's adoption of Apache Pulsar for building a scalable event-driven system with an event-sourced architecture. They chose Pulsar over Kafka due to its operational advantages and compatibility with reactive, non-blocking libraries. Key features considered were tiered storage, flexible subscription models, authorization methods, and ease of setup. Merkushev advises organizations considering Pulsar to understand the different subscription models and experiment in a real environment. Future use cases for Vivy include cross-region replication and leveraging Pulsar functions for international setups.

The text discusses the evolution of running databases on Kubernetes, from initial skepticism to a resounding "Yes!" in cloud native environments. It highlights the challenges faced and how they were resolved over time, including the introduction of StatefulSets, Persistent Volumes, and Custom Resources. The author also mentions the use of Operators like cass-operator and K8ssandra for managing Cassandra databases on Kubernetes. Overall, the text argues that running databases on Kubernetes is now feasible and beneficial in modern cloud environments.

The text discusses the evolution of running databases on Kubernetes, from a resounding "No!" five years ago to a current answer of "Yes!" in cloud native environments. It highlights the journey through stages such as exploring Docker containers and Kubernetes for stateless services, encountering challenges with persistent data storage, discovering Cassandra's potential for supporting ephemeral containers, and finally leveraging advancements like StatefulSets, Custom Resources, Operators, and frameworks like cass-operator and K8ssandra. The author concludes that running databases on Kubernetes is now feasible and beneficial in cloud native environments.

The text discusses the K8ssandra project, an open-source distribution of Apache Cassandra for Kubernetes. It provides a detailed guide for developers on setting up their local environment to run K8ssandra, including information about editor and tooling installation, installation and setup of K8ssandra, hands-on exercises, and tips from maintainers. The text also covers the key file types in the K8ssandra codebase, such as YAML files for declarative configurations and Go files for utilities and tests. It provides an overview of important folders within the K8ssandra project and offers useful commands for inspecting resources and troubleshooting issues. The text concludes with a list of recommended next steps for learning more about K8ssandra, including exploring additional open-source repositories that contribute to the overall functionality provided by K8ssandra.

The text discusses the K8ssandra project, an open-source distribution of Apache Cassandra for Kubernetes. It provides a detailed guide for developers on setting up their local environment to run K8ssandra, including editor and tooling installation, installation and setup of K8ssandra, hands-on exercises, and information from maintainers. The text also covers the various file types in the K8ssandra codebase, such as YAML files, Go files, HTML, Markdown, CSS, shell scripts, and Python scripts. Additionally, it provides tips for using command line tools like kubectl to view important logs and gather information about pods and configurations. The text concludes with a list of recommended next steps for learning more about K8ssandra.

This article discusses various performance tracing and profiling tools for Java applications when major code modifications are not possible. BTrace is a tool that compiles and dynamically inserts Java code into running applications, allowing developers to hook into execution paths of their apps. async-profiler is an open-source profiler designed for low overhead and suitable for running in production systems. It uses performance events and HotSpot-specific APIs to measure CPU cycles, cache hits/misses, and Java heap memory allocations. jstack prints Java stack traces for a running Java app and can be run against core files and remote servers. These tools provide valuable insights into the behavior of Java applications when debugging is not an option.

Debugging and troubleshooting Java applications can be challenging when major code modifications are not possible. This article explores various performance tracing and profiling tools that can be used on existing versions of software. BTrace is a tool for understanding Java application behavior by compiling and dynamically inserting Java code into running applications, allowing developers to hook into execution paths and Java runtime components. async-profiler is an open-source, low-overhead profiler suitable for production systems that measures CPU cycles, cache hits/misses, and Java heap memory allocations. jstack is a standard tool shipped with the JDK that prints Java stack traces for running applications and can be used against core files and remote servers. These tools provide valuable insights into application behavior and help solve difficult problems when major code modifications are not feasible.

As a DataStax Developer Advocate, the author's role is to assist teams in providing an excellent experience with Cassandra and related products. Datastax Astra is a multi-cloud Database as a Service (DBaaS) that offers robust free tiers for running small production workloads or personal projects without requiring credit card information. The platform supports CQL, a slightly different query language from SQL, but Stargate, an open source product, provides REST, GraphQL, and document APIs to interact with data. The author has developed an authentication plugin for HTTPie, a tool designed for REST API interaction, which can be used in conjunction with Astra. Instructions are provided on how to set up the environment using this plugin.

The text discusses DataStax Astra, a multi-cloud Database as a Service (DBaaS) that offers a free tier. It highlights Stargate, an open source product by DataStax that provides REST, GraphQL, and document APIs for interacting with Cassandra databases. The author also introduces an authentication plugin for HTTPie, a tool designed for REST API interaction, which can be used to interact with Astra's APIs. Instructions are provided on how to set up the environment and use the plugin.

DataStax, a company known for its distributed database technologies, has announced that it will build a messaging solution to complement its existing offerings. The company has been exploring the integration of messaging and streaming capabilities into its ecosystem for several years now, driven by the growing popularity of microservices-based architectures. These architectures often use a message bus to decouple communication between services, simplify replaying, error management, and peak load handling. The company has evaluated various popular options, including Apache Kafka, but found it lacking in four key areas: geo-replication, scaling, multi-tenancy, and queuing. Apache Pulsar, on the other hand, meets all these requirements to DataStax's satisfaction. Geo-replication is a crucial feature for global companies like Netflix that need to serve customers worldwide with minimal latency while adhering to data sovereignty regulations. Cassandra and Pulsar both support geo-replication natively, allowing users to choose synchronous or asynchronous replication configurations and configure topic-level replication. Scalability is another area where Kafka falls short compared to Pulsar. In Kafka, adding capacity requires copying some partitions over to the new node before it can participate in load balancing, which slows down the cluster temporarily. Pulsar introduces an additional layer of indirection and separates storage from computation, allowing for independent scaling without affecting existing data or requiring any additional work by the cluster. Multi-tenancy is another area where Kafka struggles due to its single-tenant design. In contrast, Pulsar supports native multi-tenancy, enabling administrators to manage multiple tenants across different regions from a single interface that includes authentication and authorization, isolation policies, and storage quotas. CapitalOne has written an informative article on Pulsar's multitenancy capabilities. Lastly, while Kafka offers a traditional pub/sub messaging model, it does not support queuing or dead-letter queues. Pulsar supports both pub/sub and queuing models, allowing users to balance message loads across multiple consumers without requiring them to process messages in the same order they were published. This versatility opens up opportunities for cost reduction by replacing existing AMQP and JMS systems with a single solution. In conclusion, Pulsar's architecture offers significant advantages over Kafka in terms of geo-replication, scaling, multi-tenancy, and queuing capabilities. DataStax is excited to join the Pulsar community with its acquisition of Kesque, a PaaS for Apache Pulsar, and by open-sourcing management and monitoring tools built by the Kesque team in their new Luna Streaming distribution of Pulsar.

DataStax, a company known for its distributed database technologies, has announced that it will be building a messaging solution to complement its existing ecosystem of databases. The company has started by evaluating the most popular option, Apache Kafka, and found it lacking in four key areas: geo-replication, scaling, multi-tenancy, and queuing. Apache Pulsar, on the other hand, meets all these requirements to DataStax's satisfaction. Geo-replication is a crucial feature for many applications, as it allows data to be replicated across multiple regions, ensuring local latency and compliance with data sovereignty regulations. While Cassandra supports geo-replication, Kafka does not, which can lead to increased latency for users outside the region where Kafka is deployed. Pulsar, like Cassandra, integrates geo-replication into its architecture, allowing messages to be visible to consumers across regions. Scaling is another important consideration when choosing a messaging solution. In Kafka, adding capacity can slow down the cluster before speeding it up, which may not be ideal for businesses with rapidly changing needs. Pulsar addresses this issue by separating storage and computation, allowing new nodes to be added without affecting existing data or requiring additional work from the cluster. Multi-tenancy is a feature that allows multiple users or organizations to share an infrastructure while remaining isolated from each other. This can help reduce costs by amortizing the cost of shared components across all users and simplifying administration. While Kafka does not support multi-tenancy, Pulsar has it built into its architecture, allowing for easy management of multiple tenants in different regions with features like authentication, authorization, isolation policies, and storage quotas. Finally, queuing is a messaging model that allows messages to be consumed in any order, which can be useful when the order of processing is not important. Pulsar supports both pub/sub (publication/subscription) and queuing models, making it a versatile solution for various use cases. In conclusion, DataStax's decision to build a messaging solution based on Apache Pulsar highlights the advantages it offers over Kafka in terms of geo-replication, scaling, multi-tenancy, and queuing. The company is excited to join the Pulsar community with its acquisition of Kesque, a Pulsar-as-a-service provider, and plans to open-source management and monitoring tools built by the Kesque team in its new Luna Streaming distribution of Pulsar.

The second season of the podcast "Inspired Execution" has returned with three new episodes featuring influential technology leaders discussing their career paths and strategies for success. Hosted by DataStax CEO Chet Kapoor, the podcast delves into how these executives arrived at their current roles, scaled multi-billion dollar businesses, and inspired their teams to reach their full potential. The latest episode features PayPal's EVP & CTO Sri Shivananda discussing lifelong learning. Previous episodes have included Jacqui Guichelaar of Cisco, Ravi Radhakrishnan of Wells Fargo, and Piyush Gupta of DBS Bank sharing their insights on diverse teams, risk-taking, and digital transformation.

The second season of the podcast "Inspired Execution" has returned with three new episodes featuring influential technology leaders. Hosted by DataStax CEO Chet Kapoor, the series explores the origin stories and strategies of these executives to understand how they lead multi-billion dollar businesses and inspire their teams. The fourth episode features PayPal's EVP & CTO Sri Shivananda discussing lifelong learning. Other episodes include interviews with Jacqui Guichelaar, Ravi Radhakrishnan, and Piyush Gupta, who share insights on diverse teams, managing large groups of engineers, leading a legacy bank through digital transformation, and more.

The Stargate Documents API enables users to create, get, modify, delete, and search JSON documents in a collection backed by Apache Cassandra. It abstracts away the complexities of converting JSON documents into tabular form and back again, allowing users to work with JSON over HTTP. One key benefit is rapid iteration, as it allows storing documents without any lock-in to a schema. The API shreds JSON documents for efficient storage in Cassandra and supports search functions with various filters. Since its release, performance improvements have been made, including optimizing the authentication process, enabling asynchronous execution, and enhancing the "search across collections" functionality. Future plans include supporting OR queries and using Cassandra for more multi-filter AND queries to improve performance further.

The Stargate Documents API enables users to create, get, modify, delete, and search JSON documents in a collection backed by Apache Cassandra. It abstracts away the complexities of converting JSON documents into tabular form and back again, allowing users to work with JSON over HTTP. One key use-case is rapid iteration, as it allows for storing documents without any lock-in to a schema. The API shreds JSON documents into rows that can be efficiently stored in Cassandra's sparse storage format. It also supports searching within the document and across collections using filters. Since its release, performance improvements have been made, including optimizing search functionality and reducing latency for reads and writes. Future enhancements include supporting OR queries and leveraging Cassandra more for multi-filter AND queries to improve performance further.