Operations | Monitoring | ITSM | DevOps | Cloud

The financial services industry has been under increasing pressure during the past several years to view operational resilience and their risk management postures as being symbiotic in the wake of rising operational incidents and increasingly frequent security threats.

When troubleshooting an incident, DevOps teams often get bogged down searching for errors and unexpected events in an ever-increasing volume of logs. The painstaking nature of this work can result in teams struggling to resolve issues before new incidents appear, potentially leading to an incident backlog, longer MTTR, and a degraded end-user experience.

One of the most requested features for Crash Reporting has been the ability to perform a search across all of your applications rather than by one application at a time (the default behavior). It’s not hard to see why it’s a popular feature request - rather than manually performing the same search across many applications, it would be super handy to perform one search and understand the impact of the search results across all of your applications immediately.

Kubernetes is the most popular container orchestration tool for cloud-based web development. According to Statista, more than 50% of organizations used Kubernetes in 2021. This may not surprise you, as the orchestration tool provides some fantastic features to attract developers. DaemonSet is one of the highlighted features of Kubernetes, and it helps developers to improve cluster performance and reliability.

In the monitoring industry there’s a complicated and frustrating conversation that persisted over the years: how do you deal with the enormous volume of data generated by instrumentation? On one side of the aisle, you will find a cohort of vendors and developers telling you that you have to sample data, followed immediately by another group telling you that sampling will ruin the accuracy of incident analysis. They’re both right.

Global data, analytics and technology companies such as Equifax, and their Engineering teams, depend on log analytics for a variety of operational analytics use cases, from application troubleshooting to streamlining cloud operations and regulatory compliance management. ChaosSearch is uniquely positioned to help companies like Equifax significantly reduce the time, cost, and complexity of log analytics.

The way organizations process logs have changed over the past decade. From random files, scattered amongst a handful of virtual machines, to JSON documents effortlessly streamed into platforms. Metrics, too, have seen great strides, as providers expose detailed measurements of every aspect of their system. Traces, too, have become increasingly sophisticated and can now highlight even the most precise details about interactions between our services. But alerts have remained stationary.

Today’s cloud environments rely on microservices, service meshes, containers, and orchestration tools and are too complex for traditional tools to measure and monitor performance metrics effectively. The number of interdependent services—and the inherently ephemeral nature of cloud workloads—make it challenging to identify which metrics to monitor and issues to troubleshoot down to the root cause.

SAN FRANCISCO — August 23, 2022 – InfluxData, creator of the leading time series platform InfluxDB, today announced new serverless capabilities to expedite time series data collection, processing, and storage in InfluxDB Cloud. InfluxDB Native Collectors enable developers building with InfluxDB Cloud to subscribe to, process, transform, and store real-time data from messaging and other public and private brokers and queues with a click of a button.