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jonerp : monitoring   9

The Big Picture of AIOps: Why You Need AI to Take Over DevOps
"AIOps isn’t just about streamlining cloud complexity and providing faster, more precise solutions — it’s changing the role that operations engineers play in IT. Instead of spending hours staring at dashboards, Ops engineers are freed to become engineers with developer skills, and use those skills to mentor their development teams. That gives IT Ops the opportunity to become more of a hybrid cloud service Ops team that can provide the business with a powerful platform for deploying and operating applications and services in a fully automated and self-service fashion."
ci  cd  machine  learning  monitoring  contributed  sponsored 
september 2019 by jonerp
The Current State of AIOps
"Only a few enterprises have already reached stage four, where AIOps becomes more of an advisor. “How do you actually get the system to make recommendations for additional data sources [to consider], for future potential health risks are coming down the pipe, and what recommended actions can it take.” That’s based on multivariate analysis, multidimensional analytics, and conditional automation, Piraino said. The system “can start to say, ‘if this then this,’ ‘if that then this,’ and what else can I learn before I got to the next stage?”
monitoring  feature 
august 2019 by jonerp
How to Make Sure the Next Cloud Outage Isn’t the End of Your Business
"While basic observability will transform the way you look at your cloud providers, it’s often not enough to understand the impact on your business. You could see that 1% of the requests to a cloud service are failing, but without business context you wouldn’t see that those 1% impact your largest and most important customers. This is why it’s important to look at expanding your observability to include “distributed tracing,” a tool that allows you to bring business context throughout your software’s usage of cloud services. With the context of a trace, your team will be able to see whether 1% failures are slightly annoying or a critical business problem."
cloud  services  monitoring  contributed 
august 2019 by jonerp
Security Metrics that Actually Matter in a DevOps World
"Deployment metrics measure the health of the deployment process and provide leading indicators of application stability.
Examples of deployment metrics: time-to-deploy, deployment frequency, deployment success/failure, time spent fixing failed releases, and environment configuration drift.
Elite performers in this category can deploy on demand;
Lead time metrics measure the capacity of the organization to respond to change and deliver business value (i.e. the time it takes to design and deliver requested security features).
Examples of lead time metrics: individual productivity/velocity, rework time, cycle time, time-to-value trends.
Elite performers in this category typically have average lead times <1 hour;"
devops  monitoring  security  contributed  sponsored 
june 2019 by jonerp
Add It Up: Why Salesforce and Google Bought Tableau and Looker
"Twenty-eight percent of IT professionals believe that over the next five years more sophisticated data integration capabilities will be the focus in business intelligence and analytics software development, according to SharesPost’s October 2018 survey. This was a dramatic rise from only 10% that said so in the 2017 survey. Expectations also increased about the attention that will be paid to data visualization capabilities."
data  monitoring  research 
june 2019 by jonerp
AIOps Users Found in the Wild
"AIOps early adopters have been identified. Nine percent of the 846 respondents to a Turbonomic survey have rolled out artificial intelligence or machine learning (AI/ML) IT management into production. Another 28% are “experimenting” with AI/ML for IT management, but we don’t know if that means an internal expert is creating algorithms or if a vendor product that touts AI/ML under the hood is being piloted."
machine  learning  monitoring  research  this  week  in  numbers 
may 2019 by jonerp
The Quickening: a keynote about software development velocity at New Relic’s Futurestack 2018 Conference
"It’s not all good news on the enterprise side of course. I pointed to an absolutely brutal takedown of BA in the FT for not investing in software development. This was the first big breach of the GDPR era, and this story is merciless."
uncategorized  ci  cd  devops  kubernetes  monitoring  observability 
september 2018 by jonerp
Briefing Notes: Insight Engines Takes AI To Enterprise IT - by @krishnan
"Insight Engines, the San Francisco based startup focused on making machine data actionable, announced the general availability of Cyber Security Investigator and, also, showcased how Amazon Alexa can be tapped to query from Cyber Security Investigator. In this note, we will do an analysis on this announcement."
briefing  notes  ai  artificial  intelligence  automation  cio  insights  cloud  computing  insight  engines  intelligent  platforms  it  machine  learning  monitoring 
september 2017 by jonerp
Cloud Native – Solid Roots, Time To See Beyond Kubernetes - by @fintanr
"We do want to highlight that the team running Cloud Native Con are actively trying to improve things – from organising child care, offering free passes, travel support and so forth. Their parent organisation, The Linux Foundation, has also started to put in place specific policies around speaker and panel diversity and other areas. Small steps, but steps in the right direction none the less."
business  cio  cloud  foundry  native  community  conferences  containers  developers  infrastructure  microservices  monitoring 
april 2017 by jonerp

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