Thundra, a SaaS product in the field of serverless monitoring, has released its new solution with flexible alerting capabilities included. The release would add a new feature to Thundra’s already comprehensive monitoring services, including both distributed and local tracing capabilities, log search, performance analysis, and architectural view.
“Serverless is the new evolutionary stage of cloud computing, helping the industry reduce the time, costs, and efforts required to push out software,” said Serkan Özal, co-founder and CEO of Thundra. “But monitoring serverless services is difficult because of the abstraction of lower-level architecture. Thundra comes to the rescue with its lightweight instrumentation libraries for Node.js, Python, Java, Golang, and .NET, providing detailed observability for serverless to allow the industry to seamlessly transit into this new generation.”
Headquartered in Boston, Thundra would be growing rapidly as a company. Their technology would be distinct in its ability to support both synchronous and asynchronous monitoring. Async monitoring consumes data from Amazon CloudWatch and adds no overhead to the invocation time of Lambda functions. Synchronous monitoring would add overhead, but Thundra has managed to reduce it to “less than 5ms” thanks to its data collectors spread across the US, Europe, and APAC regions.
Reducing Operational Costs
“Serverless is one of the most cost-effective services out there,” said Emrah Şamdan, VP of Products at Thundra. “Our goal is to optimize how you use serverless to further reduce costs by discovering bottlenecks. Thundra’s alerting capability is a step towards this goal. By allowing serverless users to effectively monitor their functions and quickly respond to breakdowns via alerts, Thundra can successfully reduce operational costs.”
In the coming months, Thundra plans to strengthen their product’s alerting capabilities even more – so customers will be able to set up alerts for the presence or absence of a log message. Future users will be alerted when a serverless transaction made of multiple chain invocations exceeds particular thresholds.