Maestro Blog

Self-service is one of the five keystones for any effective cloud service. This applies not only to the provisioning of services to customers but also to the way the customers organize their internal workflows. An enterprise that does not allow self-service in Cloud for its employees would definitely lose a big part of Cloud benefits, as the operational part will be complicated, slow, and not reactive enough to face the enterprise needs or arising threats properly. However, the question is – when enabling self-service, how to make sure that things don’t go out of control, especially for large teams and infrastructures? Standard Role-Based Access Control (RBAC) Typically, cloud providers allow their customers to set up role-based access to infrastructure management. In this approach, possible operations are combined into roles, typically by purpose. The users, in their turn, are combined into user groups, according to the tasks they perform and the access level they need to have. ...

Back in March, we shared an exciting story of creating a POC for a machine-learning-based infrastructure rightsizing mechanism . Naturally, such an interesting initiative and promising results could not be put aside, and we went on working on the tool to see how far we could potentially get, and – of course – if all our work is worth the benefits it could bring. From POC to a Product The initial, POC, version of Maestro Cost Advisor (that’s how we called it) was actually quite a simple one in terms of the functionality: it took the virtual machines performance metrics for 4 days, analyzed the CPU and memory load, the timelines, and suggested the following actions to the instances: Scale up Scale down Shutdown Schedule The mechanism analysed the real load on the instances and suggested new instance types based on the 90’s percentile for each parameter. The approach was good enough to prove that the mechanism would work, but definitely not enough to become a business to...

Typical infrastructure load is not homogenous. There are resources active round the clock, as well as those for which the active time is followed by idle hours. There are regular working hours for the capacities used by the enterprise teams for their daily routines, as well as peaks and dropdowns related to customer activities, Database loads, etc. And the best point here is – once a load variations are regular and predictable, they can be scheduled. Scheduling is quite a simple mechanism allowing you to get your resources turned off automatically when they are not needed, and start them back right before you are going to use them. Unlike auto scaling based on creation and termination of resources depending on the demand, scheduling is targeted to resources that are expected to have longer lifetime. As compared to other FinOps optimization procedures, it takes relatively small effort for implementation and does not bring significant changes into the infrastructure composition – s...

Cloud usage patterns, as well as the request for the specific types of cloud-related expertise, develop in cycles. Initially, the core aim of the cloud management tools was to provide the possibility to perform the basic infrastructure management operations. The ability to create, change and remove resources was enough to meet the majority of technical and business tasks. Still, the more the cloud technology developed, the more complicated the infrastructures became. Additional services arose, bringing more value to the customers, and needing more effort to track them properly.   Does wisdom come extra effort? Eventually, effective infrastructure setup, analytics, management, and optimization turned out to be not a scope for a typical IT department expert, but a set of separate specializations within the Cloud-related community. To be able to perform these operations successfully, and to take best of the cloud-native offerings, you need to spend plenty of time and effort for respec...

Selecting an effective tool for your virtual infrastructure optimization is a complex task. It needs a deep investigation of the options on the market, the details of their offerings, checking if the provisioned feature set meets your needs and expectations. Even if the vendor provides a free tier, the effort of applying the necessary configurations can take several days, and after that, you need to learn how to use the new tool properly. Thus, getting the understanding if a tool fits you may take even weeks. And the price of a mistake – if it does not – is very high, because effort and time are spent in vain – and you may be as far from your initial goal as you were at the very start. However, with Maestro you can see if it fits your business in terms of infrastructure and costs optimization in just a few days – and any intermediate result will still be helpful even if you decline Maestro at the end. So, how does this work?   Day 1. Basic resource optimization One o...

Infrastructure analytics is one of the cornerstones for effective cloud management. Each cloud provider offers its own set of features and services for such purpose. We can say that AWS QuickSight, Google Data Studio, and Microsoft BI are among the top of the native analytics and BI offerings. They are deeply integrated into their native infrastructures, provide the detailed review of the infrastructure state, events and cost, and allow to take a deep dive into details, being powered by strong internal mechanisms and AI/ML engines. However, in many cases they provide a huge volume of data which needs a BI expert to cope with, as well as may have limited customization possibilities in terms of the covered data scope. Also, if you use more than one cloud, or have private datacenters, the fact that each of these tools is limited to its vendor, may be a reason for you to find a third-party analytics tool. Here is where you may consider solutions such as CloudHealth, AppOptics, or...

During the recent years, the classic mathematics-based models used to create optimization recommendations have been empowered by Machine Learning mechanisms. This resulted in significant improvements in recommendations scope and accuracy of existing tools, as well as the creation of new ones. Having reviewed the ML-based rightsizing offerings by top cloud providers, the Cloud Competency team from Ukraine (Rostyslav Myronenko, Yevhen Nadin, Oleksandr Onsha, Bohdan Onsha) took the challenge to create their own POC. We claimed we would get the initial version of a cloud-agnostic ML-based rightsizing solution within the shortest terms – 2 weeks only. Look, what we got as a re sult! Background and Investigation Modern cloud management needs to cover a wide range of tasks and expectations from businesses and users of all kinds. Resource and cost optimization, effective performance, reliability, fault-tolerance are among them. Naturally, any cloud provider offers its own tools to help users f...