Years of losing valuable proprietary data to freak crashes and lack of remote access in their erstwhile standalone on-premise storage infrastructure have encouraged widespread adoption of the cloud among both large and small enterprises. But the cloud is still an evolving technology and cloud expertise does not come cheap. So, even though most organizations have migrated or are migrating to the cloud, they still have little idea about how to get the most out of their cloud investment. In this article, we are about to change all that.
If you want to see your cloud performance soar while reducing costs, here are five time-tested strategies that some of the most advanced cloud-handling enterprises swear by.
1. Reduce data movement
Most organizations nowadays prefer a hybrid cloud setup. This means that large amounts of data regularly travel back and forth between on-premise storage setups and cloud infra.
This entire transferring process consumes extraordinary amounts of resources and time, which scale with the volumes of data being relayed between the two types of infrastructure.
If you want to optimize your system performance, this data movement needs to be minimized. Your data needs to be classified into categories and permanently hosted in either of the two environments, depending upon the frequency of use. For example, you can host day-to-day mission-critical data on on-premise servers, while non-mission-critical data and applications can be moved to the cloud.
2. Only select instances that suit you
All leading IaaS providers offer different types of computing instances to serve varying workloads. For example, AWS provides EC2 instances that let you choose between a combination of networking, storage, CPU, and memory capabilities. While some instances are designed for general computing, there are a host of others that are optimized toward higher storage, accelerated network speeds, etc. Nobody knows your organization’s cloud computing needs better than you. So, it is best to take your time and be prudent while choosing the instances that would retain the best resources for your needs while not being too harsh on your purse.
If you choose an instance that is too small for your needs, you may save money, but that would come at the cost of compromised performance. On the other hand, too large an instance could boost your performance, but be prepared to foot exorbitant usage bills.
3. Autoscaling is your best friend
Don’t restrict your cloud computing to the default capacities of your chosen instances. Your needs can change dynamically over time, and most cloud platforms can automatically scale user resources depending on demand. In Google Cloud Platform (GCP), MS Azure, and AWS, you can easily add or remove cloud resources as your workloads change.
For example, you can use their load balancers and avoid putting too much pressure on your instances when workloads spike. You can easily set suitable autoscaling rules based on your utilization trends, and the load balancer will automatically monitor and distribute the incoming traffic across different instances.
4. Performance tracking
Any load balancer can monitor your basic traffic and workloads, but they cannot give you the metrics you need to comprehensively monitor your cloud performance. To do that, you need to collect and analyze the necessary metrics on cloud workloads and your utilization trends.
You can leverage not only built-in analytical tools within GCP, Azure and AWS but also myriad third-party services that possess real-time performance tracking capabilities to keep tabs on your cloud.
5. Caches speed up your cloud network
Transferring data between the cloud and your local network takes time, which can majorly impact application responsiveness.
One of the easiest ways to ramp up transfers is to use cloud-compatible cache services. Caches can mirror the data stored in the cloud across a content delivery network with multiple servers, thus minimizing the relative distance between data transfers. Your applications will then be able to quickly retrieve data from the nearest cache server instead of the original cloud location.
This article was originally published on our company blog.
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