Solving optimization and automation challenges with cloud-based analytics
Originally cloud platforms were supposed to simplify infrastructure management. But, as more of the corporate workloads are moved off-site, CTOs are running into new problems they have not encountered in the past.
Admittedly, cloud services have helped to reduce the amount of physical hardware infrastructure located in the local data center. But the number of virtual machines, containers and serverless apps has exploded, creating a new layer of complexity that many IT teams are unable to properly manage.
Responsibility for maintaining the underlying physical layer may have been outsourced, but the CTO is still expected to ensure the systems sat on it are operating properly. But without assistance, they will struggle – and fail – to keep applications running optimally.
When humans aren’t good enough
In order to understand how systems are performing, you need to collect – and analyze – operational data from each virtualized asset. Attempting this process manually is impossible, however, particularly as your cloud environment generates so much "white noise".
Deploying cloud-based analytics systems provides a way to separate issues, highlighting those that really do require attention. These systems typically use machine learning (ML) to establish a baseline of operations by monitoring security, data access, general network traffic etc. Any anomalous behavior will then be identified automatically, raising a request for further analysis by your engineers.
Leave it to the machines
Cloud-based analytics provides several significant benefits for your business:
1. Vast data processing capabilities
Manually tracking issues in system event logs, for instance, is extremely time-consuming, and your engineers would be quickly overwhelmed. They also won't necessarily remember historical events and their similarities to current issues.
In harnessing the power of the cloud however, hosted analytics can analyze data sets of virtually any size. Machine learning algorithms will establish an operating baseline for each specified system, and automatically identify anomalies.
2. Automated prioritization
Using an established baseline, cloud analytics can monitor new issues and assess their severity based on previous events and deviation from the norm. Your engineers are then alerted to potential problems and supplied with an accurate estimate of severity too.
Which means that your engineers are free to work on other strategic projects, until the analytics system identifies a more pressing task and that important jobs requiring intervention are never masked by lesser issues. This is particularly true of automated cloud security analytics, allowing your team to respond quickly and appropriately before systems are breached or data is lost.
3. Continuous performance monitoring
Declining system performance is often not noticed until the issue becomes severe. It then takes much longer to troubleshoot and fix the root cause, adding to the cost of the slowdown.
As already mentioned, an analytics service can be used to establish a baseline – but this also gives an indication as to the overall health of each system. You can use the baseline to assess performance and to identify opportunities for optimization too. This provides opportunities to increase performance, reduce cloud resource usage (and therefore cost) and to improve the overall end user experience.
An important investment
Given its potential to help improve operations, efficiency and costs, cloud analytics are an important investment for your business as it continues its transition to the cloud. Your job will not magically become less complex, but automation and analytics will help you ensure resources are allocated most effectively to help with your strategic growth plans.
Further value can be realized by outsourcing functions to Navisite Cloud Professional Services. Offloading low-level maintenance allows your in-house team to focus resources on strategic projects for instance. We can also work alongside your team to interpret the results of your cloud analytics, turning raw data into actionable insights for instance. And we can help to secure your cloud operations against loss, theft and outage.