Cloud
Data & AI
In today’s digital world, businesses rely heavily on their platforms to stay connected to customers, partners, and employees. If a platform experiences downtime or interruptions, it can cause significant issues for everyone involved. That’s why it’s essential for platform engineers to prioritize high availability when designing and implementing platforms. In this article, we’ll discuss the importance of high availability in platform engineering and how it can be achieved through redundancy, fault tolerance, and load balancing.
What is High Availability?
High availability (HA) is a measure of a system’s ability to remain operational over long periods of time without experiencing any failures or outages. A system with high availability is one that has been designed with redundancy and fault tolerance in mind — meaning that if one component fails, another can step in and take its place. This ensures that the system remains available at all times.
Common Causes of Downtime
There are many common causes of downtime that can impact users’ experience and business operations. These include hardware failures due to overheating or power outages, software bugs or glitches, cyberattacks like malware or ransomware, human errors during deployment or configuration changes, natural disasters like floods or earthquakes, and data center outages due to network connectivity issues.
Ensuring High Availability
Platform engineers have the responsibility of ensuring their systems remain available at all times. To do this requires understanding the benefits of redundancy, fault tolerance and load balancing — all key components of any architecture designed for HA. Redundancy means having multiple instances of a component running concurrently so that if one fails the other can take its place — thus reducing downtime and increasing reliability. Fault tolerance involves anticipating failure scenarios by putting safeguards in place to ensure failure-proof operation even if a component does fail — such as having backup servers ready to take over should the primary server go down. Lastly, load balancing distributes workloads evenly across different resources so that no single resource becomes overloaded—which helps reduce latency and improve performance overall.
Best Practices for High Availability
Aside from utilizing redundancy, fault tolerance and load balancing strategies there are also best practices engineers should follow when ensuring high availability including monitoring processes closely; proactively identifying potential points of failure; creating disaster recovery plans; testing systems regularly; automating processes where possible; minimizing manual interventions; using software tools like application performance management products; using cloud-based services where possible; training staff on HA processes; implementing security measures such as firewalls; providing regular maintenance updates; and keeping track of performance metrics such as response time and uptime percentage.
Examples
Many companies have successfully implemented HA strategies into their platform engineering practices - such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, Apple iCloud, Facebook, Netflix, Twitter, etc. All these companies have adopted various methods for ensuring their platforms remain highly available at all times—from deploying redundant clusters to running automated tests—and have reaped the rewards from doing so - improved user experience, increased customer retention rate etc.
Ensuring high availability in platform engineering is an essential part of every successful business today. By understanding common causes of downtime—and taking proactive steps like employing redundancy techniques—engineers can help ensure their systems remain reliable at all times while improving user experience along the way. Additionally, by following best practices such as monitoring processes closely and implementing disaster recovery plans, they will be better prepared should an outage occur, which will ultimately lead to improved business operations overall.
