Today was a very exciting day for Logz.io, as we held ScaleUP 2021 – our second annual user conference – dedicated to elevating our customers’ success, discussing best practices for modern observability, and unveiling Logz.io’s latest product updates. These product advancements were presented by our Co-Founder and VP of Product Asaf Yigal, and members of the Logz.io software engineering team.
Tucker Callaway is the CEO of LogDNA. He has more than 20 years of experience in enterprise software with an emphasis on developer and DevOps tools. Tucker fosters a DevOps culture at LogDNA by tying technical projects to business outcomes, practicing extreme transparency, and empowering every person in the company to contribute.
As Logz.io prepares to hold its annual ScaleUP user conference tomorrow, celebrating another amazing year of customer success and continued advancement of our observability platform, we’ve got exciting news to share about our involvement with the OpenSearch project.
Stanza is a robust log agent. GCP users can use Stanza for ingesting large volumes of log data. Before we dive into the configuration steps, here’s a matrix detailing the functional differences between all the common log agents used by GCP users. Stanza was built as a modernized version of FluentD, Fluentbit, and Logstash. GCP users now have the ability to install Stanza to their VMs/ GKE clusters to ingest logs and route them to GCP log explorer.
Ask any DevOps engineer, and they will tell you about all the alerts they enable so they can stay informed about their code. These alerts are the first line of defense in the fight for Perfect Uptime SLA. With every good solution out there, you can find plenty of methods for alerting and monitoring events in the code. Each method has its own reasons and logic for how it works and why it’s the best option. But what can you do when you need to connect two opposing methodologies? You innovate!
We're a small team of engineers right now, but each engineer has experience working at companies who invested heavily in observability. While we can't afford months of time dedicated to our tooling, we want to come as close as possible to what we know is good, while running as little as we can- ideally buying, not building. Even with these constraints, we've been surprised at just how good we've managed to get our setup.
Loki 2.4 is here! It comes with a very long list of cool new features, but there are a couple things I really want to focus on here. Be sure to check out the full release notes and of course the upgrade guide to get all the latest info about upgrading Loki. Also check out our ObservabilityCON 2021 session Why Loki is easier to use and operate than ever before.
The need for relevant and contextual telemetry data to support online services has grown in the last decade as businesses undergo digital transformation. These data are typically the difference between proactively remediating application performance issues or costly service downtime. Distributed tracing is a key capability for improving application performance and reliability, as noted in SRE best practices.
When it comes to comparing all of the best solutions for log management and analysis it can be incredibly difficult to compare key features and pricing per annum side by side to see what solutions you should consider trialling.
