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Matching Incident Management Roles and Responsibilities to Process

xmatters

Since 2018 we’ve made subtle but important changes to our architecture, and to how we approach deployments. First, we completed a move from our own hosted data centers to Google Cloud Platform (GCP). This gave us a more dynamic architecture which could be scaled to customer needs much faster than a traditional datacenter.

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How to Effectively Scale Up Your App To Handle 1 Million Users?

Xicom

In simple words, if you are already managing the workload on the cloud and still need to expand its efficiency then you need to use additional services to manage the load. This is where you need to expand your cloud architecture by adding more units of small capacity to spill the workload on multiple machines.

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The Rise of Managed Services for Apache Kafka

Confluent

Sizing is the art of measuring each component of architecture and understanding what the ratio of growth and shrinkage of that component is when there is a need to scale up and down. A good example would be a company that heavily uses GCP as their cloud provider, but wants to use Kafka from Confluent Cloud.

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Egnyte Architecture: Lessons learned in building and scaling a multi petabyte content platform

High Scalability

Over time, costs for S3 and GCS became reasonable and with Egnyte’s storage plugin architecture, our customers can now bring in any storage backend of their choice. To add elasticity, reliability and durability, these data centers are connected to Google Cloud platform using high speed, secure Google Interconnect network.