The Need
Cloud computing makes vast computing resources available for systems and can uncover bottlenecks in your architecture as servers are added to a system. Whether you have moved your system to a cloud platform or have a non-cloud implementation that requires scale, porting existing architectures directly to the cloud architectures does not mean the system can take advantage of additional resources. These problems can be painfully exposed when opening your system to additional load. Taking advantage of cloud resources often requires changes in your system architecture to scale or using new system components to solve big data problems that previously took too long to process. With our Cloud Scale service we can upgrade your system's scalability.
Our Solution
Solving scalability needs and big data problems are two major benefits businesses see in moving to the cloud. Upgrading systems to cloud scale requires careful assessment of technical options and implications for the current code base, system architecture, and ability to monitor and manage the solution. Whether your need is to scale or process big data sets there are a variety of options to solve system problems.
Some of the technologies being used to cloud scale applications include:
- Distributed data caches to reduce database bottlenecks
- Map/reduce frameworks for distributing workloads across servers
- Newer high performance, scalable databases
- Database sharding to increase performance and scalability of very large databases
Our experienced cloud architects will conduct a thorough evaluation of your system to come up with options to change your system based on your scalability requirements and recommend the best approach. We will sort through the component options for the approach and select the one that best matches your technical needs and business requirements. Selecting the right off the shelf component requires evaluating the system refactoring necessary to integrate the new component. There are timeline, performance, reliability, scalability and manageability implications that weigh into the selecting new components for your architecture. We will make sure you understand the trade-offs to choose the right solution.
Distributed data cache and data grid technologies such as Memcache, OSCache, EHCache, Coherence, and Terracota can scale Web applications where database performance has become a bottleneck. These frameworks provide fast, multi-threaded, clustered in-memory caching and disk caching of frequently accessed content and data. For applications where database access is a bottleneck they can improve scalability to near linear in the application tier, lowering the database load per user and improving site performance.
We develop systems in an iterative fashion producing incremental measurable results. This approach helps assure your needs are met by testing new features to get feedback and the scalability of intermediate deliverables versus requirements. Based on these results, features will be refined and the system tuned to improve performance, scalability, and manageability.
