Packet loss is a common problem in computer networks that can have a significant impact on network performance and business productivity. When data packets are lost through the network, the data they contain needs to be retransmitted, which can slow down data transfer rates and cause interruptions in real-time applications like video conferencing and voice calls.

When operating a larger business or project, one problem comes quickly apparent: How can I know that my servers and their applications are up and the performance is good across the board? The answer is, of course, monitoring software.

At ScienceLogic, we’ve built our customer operations to ensure our customers have an excellent end-to-end customer experience, with a rock-solid plan for improving our customers’ ability to meet and exceed their desired business outcomes. And well, we must be doing something right: ScienceLogic has been recognized in this year’s TrustRadius ‘Best of’ Awards—through our customer’s direct feedback.

Grafana Tempo 2.0 is finally here, and it’s being released with two new important features. It took us longer than we would have liked to get this release going, but it turns out that rewriting your backend AND building a new query language is quite difficult. Thanks to a massive team effort, we are proud to release Tempo with support for TraceQL and with Apache Parquet as the default backend storage format. Read on to get a quick overview of this huge release.

Here at Grafana Labs, we aim to create products which integrate well with open standards and are easy to install everywhere. Today, we’re excited to announce Grafana Agent v0.31, which allows you to connect to even more types of observability signals for both scraping and remote writes. And to help you install the Agent more easily, there is now an official Windows Docker image and an official Helm Chart. Here’s a breakdown of the latest features and upgrades in Grafana Agent v0.31.

Stack traces show us exactly where an exception occurred, but you can still be left wondering: What arguments or state caused the exception to occur? If you can reproduce the issue locally with a debugger attached you’ll have access to these local variables, but with Sentry you can identify the exception location without needing to reproduce the issue locally. By including local variables with stack traces, Sentry events become much closer to the full debugging experience.

Imagine starting your car in the morning and having your attention captured by a little red check engine light. After expressing frustration in your own unique way, your next objective is to determine why this little light has brought darkness to your morning. Your owner's manual clearly outlines how to operate and routinely maintain your vehicle, but all you know about this little light is that you’ll soon be meeting your local mechanic.

Network observability is critical. You need the ability to answer any question about your network—across clouds, on-prem, edge locations, and user devices—quickly and easily. But network observability is not always easy. To be successful, you need to collect network telemetry, and that telemetry needs to be extensive and diverse. And once you have that raw telemetry data, you need to interpret it.

Back in October 2022, our Founder and CTO Paul Dix announced the limited release of InfluxDB IOx, our new database engine. After several months of beta testing, we’re excited to announce the next phase of our database engine: general availability. As of today, InfluxDB IOx releases to the rest of the world as the new and improved InfluxDB Cloud.

Some things are inevitable, like Thanos, paying taxes, and change. While it would be nice to simply snap our fingers and deliver new products, things aren’t so simple in the real world. InfluxDB has been the leading time series database since January 2016. But we’re not content to rest on our laurels. The quest to improve InfluxDB is constant and ongoing. As of today, we’re beginning the rollout of an all-new and improved InfluxDB Cloud powered by IOx.