14 Apr
Chaos Engineering & Autonomous Optimization combined to maximize resilience to failure
This blog is co-authored by Kyle McMeekin, Head of Channel at Gremlin. Today’s enterprises are struggling to cope with the complexities of their environments, technologies, and applications. On top of these challenges, they face faster release rates, and the need
30 Mar
How to leverage ML-based optimization to balance Kubernetes performance, resilience and cost-efficie...
Stefano Doni (Akamas CTO) was one of the guest experts for the CMG virtual event on “Cloud’s top trends for 2022”. During his speech, Stefano describes how to address the challenge of ensuring that cloud-native applications get optimized in terms
22 Mar
Using ML to automatically optimize Kubernetes for cost efficiency & reliability
Stefano Doni (CTO Akamas) presented his talk during the Meetup hosted by IBM Research for the Cloud Technology in the North, on March 14th. During his speech, Stefano covers key Kubernetes resource management concepts and demonstrates how machine learning techniques
17 Feb
Beware of Kubernetes autoscaling if you want your services to be reliable and cost-efficient
Many companies delivering services based on applications running on cloud face much higher costs than expected. The problem is that over-provisioning is too often the approach taken to minimize risks, in particular when development and release cycles are getting shorter
04 Nov
Let the machines optimize the machines
Efficiency is one of Kubernetes’ top benefits, yet companies adopting Kubernetes often experience high infrastructure costs and performance issues, with applications failing to match latency SLOs. Even for experienced Performance Engineers and SREs, sizing of resource requests and limits to
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