Prometheus and Grafana are two monitoring tools that, when combined, provide all of the information DevOps and Dev teams need to build and maintain applications. Prometheus collects many types of metrics from almost every variety of service written in any development language, and Grafana effectively queries, visualizes, and processes these metrics.
While checking in recently with one of Anodot’s newest clients, I got the sort of feedback that every product owner loves hearing. I asked, “During this past month, have you been able to check alerts triggered for your region? Do you use them? Do you have any feedback?” They replied, “The alerts are spot on. Thanks all.” The company then went on to adopt Anodot across more teams. So why are we so obsessed with alerts being spot-on?
Logs are a wealth of information containing meta-data from IP addresses, User Names, and error codes. While this is all extremely helpful, the task of understanding all this can seem overwhelming at times to an untrained eye. Other times, corporations might have additional resources they would like to enrich their logs with, i.e., adding a department name to a log message that depends on the username in the log.
Cloud computing, mobile devices, and IoT technologies continue to evolve and proliferate. As a result, businesses are generating and collecting more data than ever before. Data is generated and stored every time a customer interacts with a website or device. Savvy companies understand the importance of capitalizing on that data. It enables them to enhance customer experiences and increase profitability, among other countless benefits.
Regular expressions can be crucial for wrangling log data efficiently. You may want to extract specific data from your logs to make it easier to analyze and visualize. Sometimes you might want to capture an email when a particular message is logged. Other times, you may find yourself needing to hide sensitive data in logs before they are saved. And more often than not, you need to match using a RegEx pattern rather than an exact text search. This guide is split into three parts.
Using percentages when performing data analytics is an essential approach to effective numeric comparison, especially when the data in question demonstrates drastically different sample sizes or totals. Percentages allow for a quick and accurate understanding of how much data sums have changed across a dimensional category like a range of time, geographic regions, product lines, etc.
At AWS re:Invent recently, we excitedly announced Logz.io Infrastructure Monitoring – our new Grafana-based monitoring product! This product is the third pillar of our cloud observability platform, together with Logz.io Log Management and Logz.io Cloud SIEM.
Any system connected to the Internet is vulnerable to malicious attacks and breaches. If it’s online, there’s someone out there trying to break into it and do something bad with it (usually stealing data). Plain and simple. To protect your most valuable assets, you need bulletproof security measures, a skilled SecOps team, robust investigation tools, and reliable prevention/mitigation strategies.
