Today at o11ycon+hnycon—right now, actually, if you’re reading this blog when it was posted—we’re announcing several new Honeycomb features during the keynote. Our industry and community have come a long way since we burst onto the scene, and I’m delighted to give you another version of Honeycomb that continues to demonstrate what’s possible with observability. And it includes metrics.
Elastic Cloud on Kubernetes (ECK) is an easy way to get the Elastic Stack up and running on top of Kubernetes. That’s because ECK automates the deployment, provisioning, management, and setup of Elasticsearch, Kibana, Beats, and more. As logging and metric data — or time series data — has a predictable lifespan, you can use hot, warm, and cold architecture to easily manage your data over time as it ages and becomes less relevant.
Real-time processing provides a notable advantage over batch processing — data becomes available to consumers faster. In the traditional ETL, you would not be able to analyze events from today until tomorrow’s nightly jobs would finish. These days, many businesses rely on data being available within minutes, seconds, or even milliseconds. With streaming technologies, we no longer need to wait for scheduled batch jobs to see new data events.
The results of our 2021 State of IT Operations Management survey are now available for the UK! Some common themes emerged with our US survey results published in April: Tool sprawl is real in IT operations departments in both countries as ops teams wrestle with multiple tools and report that legacy tools are holding them back from innovating. UK and US IT teams will both look to adopt digital operations platforms to combat tool sprawl, driven by better capabilities for AIOps and automation.
The Splunk Threat Research team recently developed a new analytic story to help security operations center (SOC) analysts detect adversaries executing password spraying attacks against Active Directory environments. In this blog, we’ll walk you through this analytic story, demonstrate how we can simulate these attacks using PurpleSharp, collect and analyze the Windows event logs, and highlight a few detections from the May 2021 releases.
On Tuesday June 8th, the Content Delivery Network Fastly experienced an outage that made large swaths of the web unavailable for nearly an hour. To focus on the positive, this outage can serve as a wakeup call for Observability teams, because it shows how much modern sites depend on resources beyond their immediate control, and how hard it is to "observe" these kinds of issues with an incomplete Observability mindset.
“Mean time to X” is a common term used to describe how long, on average, a particular milestone takes to achieve in incident response. There’s mean time to detect, acknowledge, mitigate, etc. And then there’s the elusive “mean time to recover,” also known as “MTTR.” MTTR, a hotly debated acronym and concept, measures how long it takes to resolve an incident on average. The problem with MTTR, though, is that it doesn’t matter.
While many statistics are floating around the web, let's consider slow page speeds from a more personal viewpoint. How many times have you waited for a web page to load, then felt frustration, anger, or even desperation as it crawled? In addition, the experience may have even given you a negative impression of the website, possibly to the extent you never want to load it again. With over 1.8 billion websites in existence, slow websites are very likely to lose precious visitor traffic.
