|
By Mohana Ayeswariya J
When a production incident strikes, a sudden latency spike, a cascading API failure, a service returning 500s at scale, every minute of downtime has a cost. Root cause analysis (RCA) is the process that turns that chaos into a clear answer: what actually broke, and why. Not the symptom that triggered the alert. The underlying cause.
|
By Mohana Ayeswariya J
A critical production alert wakes you up: p99 latency just hit 4 seconds. You drag yourself to a terminal, open five dashboards, start correlating log timestamps with trace IDs, dig through 47,000 log lines across eight services, and 90 minutes later, you finally find the culprit: an N+1 database query introduced in a deployment that shipped four minutes before the spike started. An Atatus AI SRE Agent would have identified that root cause and drafted a remediation plan in 28 seconds. Not approximation.
|
By Mohana Ayeswariya J
Modern engineering teams are drowning in telemetry data. A mid-sized Kubernetes cluster running 50 microservices can generate millions of log lines per minute. Add distributed traces, Prometheus metrics, cloud provider events, and application-level instrumentation and you're looking at terabytes of observability data every day. The problem isn't just volume. It's what you do with it.
|
By Mohana Ayeswariya J
Your logs know too much. Every debug statement, every traced request, every APM span can carry the risk of capturing something they shouldn't. A customer email. A JWT token. A credit card number. An API key that was never meant to leave your payment service. It doesn't look like a breach. There's no alert. Your observability platform just quietly accumulates sensitive data like indexed, replicated, and accessible to every engineer with log query access.
|
By Mohana Ayeswariya J
Your dashboards are green. Your thresholds are calm. Then a cascade failure starts and you don't know until users flood your status page. Traditional monitoring is reactive by design. Anomaly detection in observability changes that equation entirely.
|
By Mohana Ayeswariya J
Your on-call engineer gets paged. A critical service is down. Error rates are spiking. They open Sentry for errors. Flip to Grafana for metrics. Pivot to Kibana to search logs. Then jump to Lumigo, but that only covers the Lambda functions, not the Node.js backend throwing the actual errors. Three tabs become five. Five become eight. Half the incident is gone and your team is still piecing together what happened instead of fixing it. Sound familiar?
|
By Pavithra Parthiban
In microservices and cloud-native environments, vulnerabilities buried in transitive dependencies or runtime behaviors can go undetected for weeks. During that time, your attack surface keeps expanding and production systems remain exposed. The longer remediation is delayed, the greater the risk of exploitation, compliance failures, and operational disruption.
|
By Aiswarya S
Splunk isn't bad software. It's genuinely powerful. But in 2026, a lot of engineering teams are asking a fair question: are we getting $300K worth of value out of this? More often than not, the answer is no. We went through 15 alternatives - read the docs, tested where we could, and talked to engineers who made the switch. This is what we found.
|
By Janani
By incorporating observability tools into your stack, you can better understand how your complex infrastructure operates, reduce downtime, and empower developers to identify and fix problems quickly. However, it now takes considerably more work, time, and money to build the best observability tools for your infrastructure and applications. According to a Splunk survey, over half of the firms polled employ eight or more observability tools.
|
By Pavithra Parthiban
New Relic and Splunk are two prominent tools in the world of observability and monitoring, each serving distinct purposes. New Relic is used for Application Performance Monitoring (APM), offering a full-stack observability platform. It is important to note that New Relic is not a SIEM tool, its primary focus is performance monitoring. On the other hand, Splunk is used for log management, machine data analytics, and is widely utilized as a SIEM tool.
- May 2026 (5)
- March 2026 (2)
- February 2026 (2)
- January 2026 (9)
- November 2025 (11)
- October 2025 (8)
- September 2025 (19)
- August 2025 (13)
- July 2025 (12)
- June 2025 (8)
- May 2025 (3)
- April 2025 (5)
- March 2025 (8)
- February 2025 (4)
- January 2025 (15)
- December 2024 (10)
- November 2024 (4)
- October 2024 (3)
- September 2024 (3)
- August 2024 (3)
- July 2024 (2)
- June 2024 (7)
- May 2024 (4)
- April 2024 (4)
- March 2024 (16)
- February 2024 (11)
- January 2024 (13)
- December 2023 (4)
- November 2023 (11)
- September 2023 (7)
- August 2023 (13)
- July 2023 (9)
- June 2023 (7)
- May 2023 (2)
- April 2023 (8)
- March 2023 (6)
- February 2023 (8)
- January 2023 (6)
- December 2022 (10)
- November 2022 (7)
- October 2022 (3)
- August 2022 (9)
- July 2022 (14)
- June 2022 (10)
- May 2022 (8)
- April 2022 (5)
- March 2022 (5)
- February 2022 (8)
- January 2022 (8)
- December 2021 (3)
- November 2021 (5)
- October 2021 (6)
- September 2021 (7)
- August 2021 (7)
- July 2021 (9)
- June 2021 (19)
- April 2021 (2)
- March 2021 (3)
- February 2021 (4)
- January 2021 (3)
- December 2020 (2)
- March 2019 (2)
- November 2017 (1)
- October 2017 (1)
- September 2017 (1)
- May 2017 (1)
- March 2017 (1)
- February 2017 (1)
- January 2017 (1)
- October 2016 (1)
Seamlessly monitor your entire software stack. Gain end-to-end visibility of every business transaction and see how each layer of your software stack affects your customer experience.
Atatus builds performance monitoring infrastructure for every online business. We automate the annoying parts of error tracking and performance monitoring. Atatus supports PHP, Node.js, JavaScript, Angular, React & more frameworks.
Atatus is a SaaS-delivered application performance and error tracking solution, delivering full-stack visibility for all your apps. Our platform is able to dynamically collect millions of performance data points across your applications so you can quickly resolve issues, and improve digital customer experiences. And all of this happens in real time, in production, with cloud or on-premise deployment flexibility.
Get deeper insight into performance issues and crashes affecting your apps using Atatus's performance monitoring and error tracking service. Try it for free.