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How to Fight Alert Fatigue with Synthetic Monitoring: 7 Best Practices

It’s 1am, and something has gone very wrong. The head of sales is in the incident response channel because our top customer is reporting a system-wide outage. Everyone’s running around trying to figure it out. As you look at service maps and traces, you get a sinking feeling. Earlier the previous evening, you got an alert that user-access-service was running out of memory.

Top tips: Wearable tech etiquette in the workplace

Top tips is a weekly column where we highlight what’s trending in the tech world today and list ways to explore these trends. This week, we’re exploring wearable tech etiquette at the workplace. Prioritizing face-to-face human connection is practically nonexistent at this point, making it difficult to nurture collaborative environments. Picture yourself entering a public setting like a restaurant, a busy train, or your workplace. What do you see?

Alberto Gomez joins as CPO of Checkly and Tim Nolet will become Chief Evangelist

Today, I’m thrilled to announce two changes to our leadership team. We at Checkly aim to deliver the best synthetic monitoring platform that allows you to identify and resolve issues 10x faster. I’m proud to have crossed that 1,000-customer mark and aim to enhance your experience even further as we are just getting started and are excited about what technologies like Open Telemetry, Clickhouse and others will enable us to do in the future.

And What About my User Experience?

Monitoring backend signals has been standard practice for years, and tech companies have been alerting their SRE and software engineers when API endpoints are failing. But when you’re alerted about a backend issue, it’s often your end users who are directly affected. Shouldn’t we observe and alert on this user experience issues early on? As frontend monitoring is a newer practice, companies often struggle to identify signals that can help them pinpoint user frustrations or performance problems.

The role of secure data storage in fueling AI innovation

Artificial intelligence is the most exciting technology revolution of recent years. Nvidia, Intel, AMD and others continue to produce faster and faster GPU’s enabling larger models, and higher throughput in decision making processes. Outside of the immediate AI-hype, one area still remains somewhat overlooked: AI needs data (find out more here).

AI realism (part two)

Emotions are running high about AI technologies. In this 2-parter, I do my best to make a rational case for the state of AI, and how we can respond to it. This is the second part; catch up with part one here. Today, we’ll talk about developing a company culture that thrives on experimentation and unpredictability. I’ll describe the conditions that can keep a product company nimble and healthy during a period of rapid change, enabling it to take advantage of emerging technologies.

Monitor Complex User Flows With Checkly's Multistep Checks

With an ever-growing market of digital products, it is becoming increasingly important for every business to ensure a high level of customer satisfaction. In the past, companies might have been able to get away with slow or messy websites. Today, if a customer gets frustrated even once, they will likely abandon your product in search of a better replacement.

Monitor Complex User Flows with Checkly's Multistep Checks

Learn how Checkly's new multistep checks help you to decrease incident response times with synthetic monitoring. Use multistep checks to chain and manage multiple API requests, run custom code for response validation, and get accurate alerts when incidents occur. This video explains how to create a multistep check to monitor a RESTful API from scratch. Do you have questions? Join our vibrant Checkly community on Slack and explore further!