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Improve MTBF and MTTR for your Application Platforms by using MESH Observability

When businesses look at how best to understand the performance levels of their platforms, some of the best incident management metrics to look at are Mean Time Between Failures (MTBF) and Mean Time ToResolution(MTTR). These two measurements will give an excellent indication of the health and speed of the system, as well as the ability of the platform to take care of any anomalies that have been detected or to flag them up for others to take action to resolve them.

Charmed Spark beta release is out - try it today

The Canonical Data Fabric team is pleased to announce the first beta release of Charmed Spark, our solution for Apache Spark. Apache Spark is a free, open source software framework for developing distributed, parallel processing jobs. It’s popular with data engineers and data scientists alike when building data pipelines for both batch and continuous data processing at scale.

10 Steps to Create a Risk Management Plan

It’s always nice to know the theory behind the practice, but sadly that’s not enough. A Risk Management plan is what will make you truly effective at avoiding risks and keeping your organization safe. Having a set of guidelines will help you map your activities, ensure the right people are held accountable, and avoid possible disruptions or fines. Don’t know where to start? Don’t worry!

The Leading Use Cases For Data Monitoring

Generally, data monitoring can be referred to as a continuous process of observing and tracking data in order to ensure its integrity, quality, and conformance with specific standards or requirements. Data monitoring often involves systematic data collection, analysis, and reporting to identify patterns, trends, anomalies, and potential issues.

Adopt a "Release-first" Approach with Release Lifecycle Management in JFrog Artifactory

Every organization has a process for building and releasing software. Smaller organizations may run a few automated tests before releasing, while larger organizations may have 100s of scans, validations, and approvals spanning everything from technical to legal. Whatever the process is, the end goal is the same: software that’s mature enough for release. The challenge is that this process is complicated, messy, and often created in an ad hoc way, changing as organizations evolve.

How Coralogix Powers Your Synthetic Monitoring with Checkly

As a leading full-stack observability platform, Coralogix enables you to gather, monitor and analyze your infrastructure and application telemetry. And Coralogix now offers synthetic monitoring for proactive end-to-end testing across development with Checkly.

How to get the best of lexical and AI-powered search with Elastic's vector database

Maybe you came across the term “vector database” and are wondering whether it’s the new kid on the block of data retrieval systems. Maybe you are confused by conflicting claims about vector databases. The truth is, the approach used by vector databases has been around for a few years.