Speedscale achieves expertise as part of Google’s Partner Advantage Program, helping SaaS companies optimize cloud price-performance ratio while scaling quality
ATLANTA, GEORGIA, UNITED STATES, May 31, 2022 /EINPresswire.com/ — Speedscale, the Kubernetes traffic replay company that can simulate production conditions, announces it has successfully achieved an Expertise in Cloud Native Application Development as part of Google’s Partner Advantage Program. Achieving this Expertise means that Speedscale has demonstrated strong customer success with Google Cloud.
Nylas, a leading name in bidirectional email sync, used Speedscale’s traffic replay capabilities to optimize its cloud price-performance ratio and continuously deliver quality releases at scale. Using Speedscale, Nylas proved:
– Google’s Tau VMs with GKE delivers over 40% better price-performance than their current cloud architecture.
– Email synchronization, the highest throughput part of their SaaS offering, improved 30x as part of their migration and continuous testing.
TESTING AT THE SPEED OF CLOUD NATIVE
“Nylas needed modern observability and QA tools to deliver highly performant, quality releases, at the speed of cloud native, which Speedscale allows us to do with confidence,” said David Ting, Nylas’ senior VP engineering, product and CISO. “With every new feature and every delivery, our developers add new nodes and microservices, more API integrations and more interdependencies that – without proper testing – could easily trigger a breakdown in API communications. Fortunately for Nylas and our customers, Speedscale provides fast API performance benchmarking and testing needed to satisfy customer demand.”
Unit, UI and manual testing are the industry standard. Yet according to the 2019 State of DevOps Report by DORA, the types of incidents that bring down production systems are often “caused by interactions between components.” The vast majority of quality automation still requires an author to painstakingly create each individual test case and maintain them, which slows delivery dramatically. By leveraging traffic to auto-generate tests and environments, Speedscale allows users to exercise their APIs on GKE and finally keep pace with development. A user can also multiply traffic to simulate high load to test Google’s Autopilot and ensure auto-scaling performs as expected.
“Speedscale’s superpower is mocking real-world traffic patterns, including spikes in volume of incoming requests and any variability in data returning from downstream services,” said Ken Ahrens, co-founder of Speedscale. “It’s like testing in production with none of the risk. You simulate production conditions in pre-prod but also understand latency, throughput and headroom of changes are within your expected bounds.”
To learn more about Speedscale’s Expertise in Cloud Native Application Development, visit https://cloud.google.com/find-a-partner/partner/speedscale-inc.
Whitepaper: Traffic Replay from the future – forecasting latency, throughput and headroom before every deploy
Case Study: Nylas Reinvents Architecture With Speedscale and GKE
Speedscale 30 Day Free Trial
Speedscale CLI, free observability tool that inspects, detects and maps API calls on local applications or containers, available at https://speedscale.com/cli-download/
Speedscale is a traffic replay framework that provides API observability and production-simulation capabilities. It provides all the benefits of testing in prod with none of the risk. In order to do this, sophisticated tests and mocks are built from real, sanitized traffic. Traffic can be multiplied to measure the golden signals of latency, throughput, saturation and errors before the code is released. 3rd party mocks can be configured to respond realistically, or with latency, network black holes and 404’s. Traffic Replay can be integrated to CICD to provide early, repeatable SLIs.
Speedscale Traffic Replay is a modern load, integration, and chaos testing framework — an alternative to legacy scripting tools which can take days or weeks to run and do not scale well for modern architectures.
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