{"id":11423,"date":"2022-11-29T07:00:00","date_gmt":"2022-11-29T15:00:00","guid":{"rendered":"https:\/\/formtek.com\/blog\/?p=11423"},"modified":"2022-05-09T15:42:18","modified_gmt":"2022-05-09T23:42:18","slug":"observability-taking-monitoring-to-the-next-level","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/observability-taking-monitoring-to-the-next-level\/","title":{"rendered":"Observability: Taking Monitoring to the Next Level"},"content":{"rendered":"\n

As businesses automate processes by using software tools like RPA and by deploying robotics in the workplace, they need a way for assessing the success of their automation efforts.<\/p>\n\n\n\n

‘Observability’ describes the measurements and analysis that can help one better understand an operational system. Observability helps us provide answers to questions asked about a phase of a process or system from which we can infer how the system is performing. Observability typically looks at data like log files, metrics and transaction traces that are created when an external input is provided to the system.<\/p>\n\n\n\n

Observability has become particularly important in being able to monitor systems like software systems based on microservices that interact with each other in complex ways. <\/p>\n\n\n\n

Often both the terms ‘monitoring’ and ‘observability’ are used, but the distinction between the two is somewhat nuanced. Monitoring tends to refer to the more basic collection of data while observability goes one step further by interpreting the data<\/a>.<\/p>\n\n\n\n

Chris Tozzi<\/a>, analyst and technical editor, wrote that <\/a>“in the past, monitoring routines focused on pretty simple and unimaginative types of data. Mostly, it was metrics like CPU and memory consumption. That has changed today. Not only has observability brought to the fore logs and traces \u2013 which, along with metrics, comprise the so-called pillars of observability, but teams are now also tracking metrics from systems and processes that they may not think of as IT resources in the conventional sense. For example, they may track metrics from their continuous delivery pipelines to measure the performance of their software delivery operations or use data about help desk response times and ticket types to contextualize data from technical systems.”<\/p>\n\n\n\n

Dhiraj Goklani<\/a>, Area Vice President of IT & DevOps, APAC at Splunk, said that<\/a> “COVID-19 has been a catalyst, greatly accelerating digital transformation, including cloud migration, app modernization and the development of net new direct-to-consumer cloud-native applications. This translates to the growing complexity of applications and cloud infrastructure, in addition to increased data flows and security concerns, combined with teams still working remotely \u2013 these are creating more challenges than ever, making observability essential.<\/em>“<\/p>\n

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As businesses automate processes by using software tools like RPA and by deploying robotics in the workplace, they need a way for assessing the success of their automation efforts. ‘Observability’ describes the measurements and analysis that can help one better…<\/span><\/p>\n

Read more ›<\/a><\/div>\n

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