How to Better Optimise Your Cloud Applications

According to Gartner, the cloud services market will grow 17.5% by the end of 2019 that totals to $214.3 billion. This is an increase from $182.4 billion in 2018.

Cloud offers a cheaper, hassle-free, and efficient way to manage voluminous data. It also provides improved scalability, agility, seamless integration, and faster configuration.

Though cloud adoption results in financial and operational excellence, the process doesn’t end with the last app being moved. There is always a need to monitor the deployed resources to ensure consistent productivity, security, compliance, and elevated ROI.

Furthermore, optimization techniques like identifying idle cloud instances and accurately meeting usage commitments help slash costs and boost application performance on cloud.

Equipped with unmatched experience in providing cloud computing services in Genève, we have listed a few other aspects of cloud optimization that help enhance application performance.

1. Choose Cloud Auto-Scaling

According to Forbes, 60% of enterprises allocate funds for additional storage space to manage huge amounts of data.

Auto-scaling is a dynamic feature of cloud computing. This attribute enables the application to automatically extend its services like virtual machines and server capacities, depending on the demand. Auto-scaling ensures that new instances are increased seamlessly with the rise in demand and decreased after the completion of such instances. This feature is pivotal in controlling operational costs in a cloud application.

Consider a situation where a campaign performs well and there is a sudden upsurge in traffic. With auto-scaling, the system will be prepared to manage this unprecedented spike.

Furthermore, as auto-scaling is geared towards offering the right number of cloud resources based on current needs, it also allows defining the minimum and maximum sizes of instance pools and scaling metrics.

2. Manage Instances Effectively

An idle computing instance may utilize a minimal part of the CPU capacity when the enterprise is being billed for 100% utilization. This results in a wastage of resources. Such idle instances should be identified and removed. The key to cloud cost optimization is consolidating computing workflows to fewer instances.

It is cardinal that the enterprise decides the size of the virtual server instances before the migration. The focus should be on reducing unused instances by defining clear rules and metrics. Organizations can also benefit from features of auto-scaling, load balancing, and on-demand capabilities.

3. Explore the Latest WANOP Systems

The latest WAN optimization systems seamlessly support cloud-based applications and can be used as a virtual service to optimize traffic and bandwidth by aggregating links. The WANOP (Wide-Area Network Optimization) systems can also be used to:

  • Shape traffic by prioritizing and allocating bandwidth accordingly.
  • Control data deduplication by reducing the amount of traffic across WAN for remote backups, replication, and disaster recovery.
  • Compress data size to limit the amount of bandwidth.
  • Cache data by storing frequently used data on a local server for faster access.
  • Monitor traffic continuously to detect non-essential components
  • Define rules and regulations for downloads and internet use.
  • Spoof protocols by grouping chatty protocols to speed processes.

4. Optimize Cloud Storage

Optimizing data storage on cloud will help better manage data from multiple sources. This can be done in the following ways:

  • Delete or Migrate Unnecessary Files after a Particular Period

Rules can be programmatically configured to shift data to other tiers or delete unnecessary data. This saves a lot of storage space. Major cloud providers implement data lifecycle management. For example in Azure, active data can be placed in Azure Blob Standard storage but if some files are being accessed less frequently, they can be shifted to Azure Cool Blob, which has a cheaper storage rate.

Also, object storage for log collection automates deletion using life cycles. An object can be programmed to be deleted after a stipulated period from its creation.

  • Data Compression before Storage

Data compression before storage reduces storage space requirements. The incorporation of fast compression algorithms like LZ4 boosts performance.

  • Check for Incomplete Multipart Uploads

Object storage includes several incomplete uploads. If an object storage bucket has a capacity of a petabyte, even a 1% incomplete upload will occupy several terabytes of space. Such unwanted uploads must be cleared.

5. Implement Cloud Analytics

Incorporating cloud analytics helps get the most from the cloud investment. It helps analyze the cloud spend and usage trends across the application. The advantages of cloud analytics are:

  • Controlled Costs

Enables right-sizing resources based on usage trends. It also offers recommendations of the best-suited resource size and estimated cost savings possible due to it.

  • Comprehensive Resource Management
  • It offers a holistic view of the spend across applications.
  • It provides intuitive insights about additional cost savings by identifying idle resources and helping realize the implementation of best practices.
  • Helps stick to a budget and triggers alerts if exceeded.

6. Incorporate a Governance Structure

A solid governance structure helps organizations to determine effective ways to monitor cloud solutions and establish best practices. A governance board can help:

  • Oversee adherence to compliance and regulatory requirements
  • Authorization levels within the cloud application
  • Scenarios wherein cloud solutions can be implemented for improvement

It also helps in curbing idle instances and monitors the efficiency of the cloud application on the whole.

7. Select Event-Driven Architectures

Server-less computing is event-driven application design. AWS Lambda, Azure Functions, and Google cloud Functions are examples of server-less cloud services.

Though servers are required to operate event-driven functions in the backend, the idea of an event-driven architecture is to slash deployment and long-term operation of instances.

Cloud providers control event-driven architectures. An appropriate code is loaded to determine software behavior or functions. This code is deployed and runs only when triggered by a real-world or programmatic event. After the function is complete, the code is unloaded and does not occupy any cloud resource

Event-driven architecture comprises event producers that generate a stream of events, and event consumers that listen to the events and respond. Event producers are decoupled from the event consumers and consumers are decoupled among themselves. In a few systems like IoT, the events need to be ingested in huge volumes through the event ingestion feature.

8. Opt for Micro Services Architecture

Monolithic applications include all the features and functions in a single executable structure. Though such an application is a proven development approach, it does include concerns about scalability and performance on cloud.

For example, if the monolithic application has reached its peak performance, a whole new instance will need to be created and deployed as a new application.

Microservices architecture addresses this concern. It splits an application into several programs. They are individually deployed, operated, and scaled. These work as APIs to provide the application’s functionality. In this case, if one API reaches its maximum performance limit, only that particular API needs to be scaled out. This proves to be a faster and more resource-efficient way to manage applications.


In the above microservices architecture, we can see independent services are self-contained and implementing a single business capability.

Wrapping Up

The cloud computing ecosystem is dynamically changing to stay on par with rising demands. Enterprises need to continuously monitor it and be creative to make the most of this platform. Though there are several optimization techniques, the key is to find the best-suited techniques that align with the goals and operational needs of the enterprise and implement them to obtain maximum benefits.

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