May 2021 Summaries

In a recent YouTube tutorial, popular coder and Datastax friend Ania Kubow demonstrates how to build a Netflix clone using Datastax Astra as the foundation and leveraging GraphQL API for communication. The video also explores slicing and pagination techniques. Notably, it includes feedback from an actual Netflix engineer who reviews the code and deployment of this clone. Viewers are encouraged to check out Ania's YouTube channel for more informative content. Reference: https://github.com/DataStax-Examples/astra-netlflix

In this latest YouTube tutorial, popular coder and Datastax friend Ania Kubow guides viewers through building a Netflix clone using Datastax Astra as the foundation and leveraging GraphQL API for communication. The video also explores slicing and pagination techniques. Notably, it includes feedback from an actual Netflix engineer. Viewers are encouraged to check out the tutorial and subscribe to Ania's YouTube channel for more coding content. Reference: https://github.com/DataStax-Examples/astra-netlflix

Apache Pulsar Heartbeat is an open-source tool designed to monitor the health and performance of Apache Pulsar clusters in real time. It addresses limitations of Prometheus metrics by generating synthetic workloads continuously across various protocols, providing insights into end-to-end system availability and latency. Key features include pub-sub tests, WebSocket availability checks, broker health monitoring, admin REST API testing, Kubernetes integration for discovering replicas, geo-replication testing, and alert generation through OpsGenie and PagerDuty integrations. Pulsar Heartbeat is available as a standalone tool or integrated into Luna Streaming and Astra Streaming services.

The text introduces serverless Astra DB and its improvements in identity and access management (IAM). New default roles have been added for easier selection based on specific use cases. Custom roles can now be created within Role Management, allowing permissions to be scoped at the organization level or specific databases, keyspaces, or tables without using CQL. Application tokens are managed at the organization level and can generate databases within an organization. These tokens do not automatically expire but can be destroyed if compromised or no longer needed. Client ID and client secret are used for authentication against databases created on or after March 4, 2021. The text also mentions that custom roles, application tokens, and organization users can be managed within Astra itself or the DevOps API, allowing automation of authentication and authorization management while maintaining easy auditing and quick changes.

Adelphi is an open-source QA tool for Apache Cassandra™ that simplifies running data integrity and performance tests on Kubernetes. It leverages pre-packaged workload generators, such as NoSQLBench, Gemini, and cassandra-diff, to create a simple and reproducible testing process. Adelphi is built on top of two main CustomResourceDefinitions: K8ssandra Cass-Operator and Argo Workflow. It spins up two side-by-side (though isolated) Cassandra clusters in Kubernetes and generates a pseudo-random workload based on the provided schema. The persisted data of both clusters is then compared as an integrity guarantee. Adelphi is currently being developed, with some known limitations around UDT/UDF support and automatic migration of schemas across major versions. Future updates will include a new UI for better user experience and data archival.

DataStax has announced the availability of Fast JMS for Apache Pulsar, a JMS 2.0 API that combines the industry-standard Java Messaging Service (JMS) API with the cloud-native and horizontally scalable Apache Pulsar™ streaming platform. This open-source solution aims to modernize JMS infrastructure, improve performance, and reduce costs. Fast JMS for Apache Pulsar supports a complete set of JMS functionality and offers superior platform capabilities compared to alternatives like ActiveMQ and Kafka. It is available under the Apache 2.0 license and can be used with DataStax's Luna Streaming Enterprise support of Apache Pulsar or Astra Streaming, their enterprise-grade Pulsar cloud service currently in private beta.

Apache Cassandra™ has gained popularity due to its high availability and scalability, supporting thousands of companies in backing their high-performance applications. Recent innovations like Project K8ssandra and Stargate have further enhanced Cassandra's capabilities. Stargate offers modern data APIs such as REST, schemaless JSON, and GraphQL, enabling developers to prototype quickly and back production applications with Cassandra using familiar APIs. It also supports multiple data models, including documents, key-value, and tabular. DataStax's Astra provides a serverless Cassandra-as-a-Service option that is free for prototyping purposes. Developers can use tools like Postman as the client interface and transition to using Stargate with existing Cassandra OSS or DSE in production environments.

The final two episodes of the second season of the Inspired Execution podcast feature conversations with technology leaders from global enterprises like PayPal, Wells Fargo, and Goldman Sachs. Topics discussed include digital transformation initiatives, inspirations, and advice for younger selves. In episode ten, Chet Kapoor speaks with Jeetu Patel about simplicity, memorability, understanding the power of compounding value, and the future of hybrid workplaces. Other episodes feature insights from leaders like Steve Mills, Aref Matin, and Greg Sly on their journeys in technology, AI and machine learning in education, overcoming adversity, trusting plans, and building sustainable data centers. To stay updated with new episodes, join the mailing list.

Apache Cassandra® has gained popularity due to its high availability and scalability, making it a trusted choice for thousands of companies running high-performance applications. Recent innovations have expanded Cassandra's capabilities beyond just being highly scalable and fault-tolerant. For example, Project K8ssandra simplifies the process of running Cassandra on Kubernetes, while Stargate offers modern data APIs for developers to use with Cassandra. This includes REST, schemaless JSON, and GraphQL, allowing for faster app development and reduced time to launch applications. Additionally, operators can leverage Cassandra as a multi-model database, consolidating their database sprawl into one platform. Stargate is the default API of Astra, a serverless Cassandra-as-a-Service by DataStax, which offers free access for prototyping purposes. Developers can use tools like Postman to interact with the cloud APIs and switch to a pay-as-you-go service when transitioning from prototype to production. For in-house deployment, operators can install Stargate to work with existing Cassandra OSS or DSE systems. DataStax offers assistance for using Stargate with their various products and services.

Apache Cassandra's shared-nothing architecture makes it ideal for deployments across multiple physical datacenters. To provide a solution that spans multiple regions and clouds, DataStax selected Kubernetes as their orchestration platform. They chose to create an ad-hoc overlay virtual application network, which consists of routing and transport components. The routing component involves assigning a unique subnet for the overlay network and using deterministic formulas to convert between pod names and virtual IP addresses. For packet transport, they use a sidecar overlay network with an init container that sets up packet routing and forwarding logic, while the sidecar proxies traffic to the right endpoint. This solution provides shared-nothing architecture, low complexity, low operational burden, and high degree of isolation between tenants.

DataStax's Adelphi project aims to simplify Apache Cassandra™ cluster upgrades by providing tools for validating current schema and comparing performance between two versions. The Argo workflow component creates necessary instances, executes operations, and monitors performance. The Python package automates tasks like generating configuration files and anonymizing schemas for public repository contribution. Adelphi is open-source, and users are encouraged to contribute their real-world schemas to help the Cassandra community develop and test applications.

DataStax has received a new investment from Goldman Sachs, validating their approach to the massive market opportunity for modern data apps on any cloud with Apache Cassandra™. The company is focused on helping enterprises and developers build and run these applications using an open data stack that delivers unique value in a rapidly growing market. DataStax's new serverless Cassandra-compatible offering, Astra, is the first and only open, multi-cloud database-as-a service, providing innovation and freedom unmatched by competitors. The investment will be used to grow sales and marketing teams, scale globally, and further develop offerings like Astra, event streaming, and other services. DataStax aims to deliver products that developers love and change the trajectory of enterprises they work for.

DataStax's Adelphi project aims to simplify Apache Cassandra® cluster upgrades by providing tools for validating current schemas and comparing performance between different versions. The Argo workflow component creates instances of both the source and target clusters, executes tests, and monitors performance. A Python package automates tasks such as generating configuration files and anonymizing schemas for contribution to a public repository. Adelphi is open-source, and contributions from the Cassandra community are encouraged to improve the project further.

In recent years, there has been a shift in why and how organizations use multi-model databases. The primary driver for adoption was the flexibility they provided in data modeling. However, as customer demands and business requirements have accelerated, developers need faster access to data without having to wait for architects to spend weeks or months on data modeling. This has led to a new focus on providing low-friction data access to developers through APIs that adapt seamlessly to application needs. Multi-model databases now need to provide organizations the ability to quickly adapt to changing app requirements and make data available for querying in the way developers want, without requiring data model optimization. This evolution is a significant shift in emphasis for multi-model databases, moving from giving architects data modeling flexibility to empowering developers with simplified data access that adapts to application requirements and accelerates time to market.

Multi-model databases have evolved from providing flexibility in data modeling to focusing on low-friction data access for developers through APIs. This shift is driven by the need for quick adaptation to changing customer demands and business requirements, making detailed planning and elaborate data modeling less effective. The new emphasis is on empowering developers with simplified data access that adapts to application needs, accelerating time to market.

DataStax Kubernetes Operator for Apache Cassandra™ manages Cassandra clusters in Kubernetes, providing configuration management, scaling capabilities, and error handling. It also handles necessary configuration changes for operations like repair and backup and restore as part of K8ssandra. This post focuses on some of the configuration management capabilities of Cass Operator through a series of examples. The first set of examples do not require any advanced understanding of Cass Operator or Kubernetes in general, while the advanced examples assume a deeper understanding of Kubernetes as they cover topics like init containers and StatefulSets. These examples demonstrate how to configure Cassandra and Kubernetes resources, including configuring cassandra.yaml and jvm-options for a Cassandra 3.11.10 deployment, managing multi-rack clusters across availability zones, specifying CPU and memory requirements for containers, adding custom labels to pods, adding environment variables to the cassandra container, and enabling remote JMX for Reaper repair operations.

DataStax Kubernetes Operator for Apache Cassandra® manages Cassandra clusters in Kubernetes, providing configuration management, scaling capabilities, and error handling. The text delves into the configuration management capabilities of Cass Operator through a series of examples that demonstrate how to configure Cassandra and Kubernetes resources. These examples cover basic configuration settings as well as advanced topics like init containers and StatefulSets. They also illustrate how to specify CPU and memory requirements for each container, add custom labels to Cassandra pods, add environment variables to the cassandra container, and enable remote JMX for Reaper. The text highlights that while Cass Operator provides flexibility in configuration management, it is dependent on implementation details of Kubernetes and Apache Cassandra.

The Data on Kubernetes Community (DoKC) has hosted over 50 meetups in multiple languages since its inception last year, with the help of MayaData and now co-sponsored by DataStax. DoKC was accepted as an official CNCF community group and will host the first ever Data on Kubernetes Day at Kubecon/CloudNativeCon Europe on May 3. The goal is to collaborate in open source communities like Kubernetes, Data on Kubernetes, Apache Cassandra, and K8ssandra to find the best solutions for cloud-native databases on Kubernetes.

The Data on Kubernetes Community (DoKC) has grown significantly since its inception last year, hosting over 50 meetups in multiple languages. MayaData and now DataStax have co-sponsored the community, which was recently accepted as an official Cloud Native Computing Foundation (CNCF) community group. The DoKC will host the first ever Data on Kubernetes Day at Kubecon/CloudNativeCon Europe on May 3rd. Community members are encouraged to collaborate in open source projects like Kubernetes, Apache Cassandra, and K8ssandra to develop the best solutions for cloud-native databases.