Operations | Monitoring | ITSM | DevOps | Cloud

In today’s high-performance data centers, “all green” dashboards can mask catastrophic issues hiding just beneath the surface. If you’re missing the microbursts, hidden oversubscription, and routing imbalances that are devastating application performance, you’re flying blind. Learn how to close these visibility gaps and shift from reactive firefighting to proactive network intelligence.

We’ve been working on a number of items here at InfluxData to give you even more options for creating visualizations and dashboards for your time series data in InfluxDB 3.

Both user and server-side monitoring are important to make your apps better. Tools that offer monitoring of just one side leave gaps in your diagnosis, causing negative experiences and reliability issues. Here are the top 10 tools you should consider based on their benefits and coverage.

For many enterprises, incident response feels like déjà vu. The same issues keep happening over and over, eating up time, draining resources, and wearing down your teams. In fact, 20-40% of IT incidents are typically recurring issues, created by unresolved underlying problems. Teams prioritize speed over permanence, patching symptoms instead of addressing the root cause. They often lack the right context, documentation, or shared knowledge to permanently fix issues.

If you’re running Calico using manifests, you may have found that enabling the observability features introduced in version 3.30, including Whisker and Goldmane, requires a more hands-on approach. Earlier documentation focused on the Tigera operator, which automates key tasks such as certificate management and secure service configuration. In a manifest-based setup, these responsibilities shift to the user.

Manually sharing mobile app builds with Quality Assurance (QA) engineers can be a tedious and error-prone process. Developers often find themselves exporting.apk or.ipa files, uploading them to Google Drive or Dropbox, and then pinging the QA team on Slack to announce the upload, all while juggling deadline and code reviews. This manual process not only slows down feedback cycles but also leaves room for human error, miscommunication, or outdated builds being tested.

Data migrations have long been a significant source of anxiety for businesses and IT teams alike. The thought of moving critical databases often conjures images of prolonged downtime, service interruptions, and the ever-present risk of data loss. Indeed, statistics show that “90% of businesses experience unexpected downtime during database migrations, leading to significant revenue loss and customer dissatisfaction”.

Kafka is too expensive and complex for 80% of users. Most Kafka usage is small-data - ~60% of clusters are sub-1 MB/s, yet teams pay big-data prices. Diskless (KIP-1150), Tiered, and Iceberg topics give Apache Kafka multiple storage classes, but they’re advanced storage primitives. They are powerful in the hands of seasoned platform teams but too complex for beginners.

In the first two parts of this series, we introduced Angular Signals and built a reactive shopping cart. Our CartService already supports core operations like adding, removing, and clearing items, as well as computing total price and item count using computed(). All of this was done without touching RxJS, subscriptions, or change detection hacks. But a real-world cart does more than tally up numbers.

If you could run public and private cloud like they were the same place, what would that unlock for your teams? That was the core message of our Navigate London keynote, and it matters just as much to readers in Singapore or Seattle as it does to those who joined us in person. For years, the industry has made you choose. Public cloud on one track. Private cloud on another. Different APIs, different skills, different bills, and a rewrite every time you move.