Dynatrace
OCTOBER 2, 2023
Limits of a lift-and-shift approach A traditional lift-and-shift approach, where teams migrate a monolithic application directly onto hardware hosted in the cloud, may seem like the logical first step toward application transformation. remove the dependency on the monolith after all testing is successful. create a microservice; 2.
Scalegrid
FEBRUARY 8, 2024
Key Takeaways Distributed storage systems benefit organizations by enhancing data availability, fault tolerance, and system scalability, leading to cost savings from reduced hardware needs, energy consumption, and personnel. They maintain fault tolerance and redundancy by replicating this information throughout various nodes in the system.
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Dynatrace
NOVEMBER 1, 2022
This measurement includes time spent testing until the service is fully functional again. This includes time your team spends investigating, repairing, and testing. MTTF measures the reliability of a network and durability of its hardware. The Dynatrace Software Intelligence platform monitors the full multicloud stack.
Dynatrace
NOVEMBER 15, 2021
Logs can include data about user inputs, system processes, and hardware states. Whether a situation arises during development, testing, deployment, or in production, it’s important to work with a solution that can detect conditions in real-time so teams can troubleshoot issues before they slow down development or impact customers.
Dynatrace
OCTOBER 1, 2021
In these modern environments, every hardware, software, and cloud infrastructure component and every container, open-source tool, and microservice generates records of every activity. Observability is also a critical capability of artificial intelligence for IT operations (AIOps). Bring observability to everything.
O'Reilly
NOVEMBER 28, 2023
Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. That pricing won’t be sustainable, particularly as hardware shortages drive up the cost of building infrastructure. Any attempt at automating customer service needs to be very carefully tested and debugged.
O'Reilly
SEPTEMBER 19, 2023
Doubly so as hardware improved, eating away at the lower end of Hadoop-worthy work. And then there was the other problem: for all the fanfare, Hadoop was really large-scale business intelligence (BI). Google goes a step further in offering compute instances with its specialized TPU hardware. Specifically, through simulation.
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