What You Need to Know: Causal Clustering
What Is Causal Clustering?
Causal Clustering is the next generation multi-site replication technology. It supports a distributed system clustering model for data centers. With Casual Clustering, you can experience better performance for remote team members and more robust replication, ensuring your teams are always up and running.
Causal Clustering Features
Causal Clustering is not new. But there are serious benefits for semiconductor organizations who adopt this technology.
With Casual Clustering, core servers always remain available. They provide a fault tolerant platform for transaction processing. Your teams can stay up and running with a simple majority of core servers functioning.
One of the main features of Causal Clustering is the ability to handle local and concurrent writes. For example, in previous HA topologies, if you are in India and your data center is in the United States, data would first need to be forwarded to the data center. Then it would be synced back before being available to the team. This wastes time. With Causal Clustering, it is written locally, with servers pulling data. There is no waiting around for data to be pushed. This saves teams time, making changes instantly available.
If a network or server outage were to happen, replica servers are guaranteed to read at least their own writes. A team may not be able to write until core servers are back up and running, but teams can stay productive. Because Causal Clustering uses a voting method (more on that later), there is no branching. This means that you would never encounter a ‘split brain’ instance where you would need to reconcile two different versioning of the same data.
Along with these features, Causal Clustering implements a simple architecture with built-in load balancing. You can set up your cluster anyway you prefer. It is easier to configure over mixed and matched topologies, making it also easier to maintain.
When it comes time to upgrade, Causal Clustering allows you to implement rolling updates. This eliminates unnecessary downtime, keeping your teams productive.
Causal Clustering Benefits for Designers
Designers are one of the most expensive asset for semiconductor companies. With Causal Clustering, they can get better performance. Local writing keeps teams moving. They can always read their own writes, and there are no inadvertent branching concerns.
Causal Clustering also helps with higher service availability. Not only can servers remain up during an upgrade, but if there is an issue, it can be isolated and resolved with minimal downtime. Teams can experience faster resolution of potential bugs and issues due to better transaction-level instrumentation.
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Causal Cluster Operations
How does Casual Clustering work? The main responsibility is on the core severs. These are equivalent to a master role in other High Availability (HA) models. Core servers replicate using the Raft protocol, which ensures that data is safe/durable before confirming a transaction. The smallest cluster of cores accepted is three. These core servers work together to vote and accept a transaction (N/2 +1).
Read replicas help scale out graph workloads from cores. They act like data caches and can execute read-only queries and procedures. Replicas are asynchronously replicated from core servers. They periodically poll upstream servers for new transactions. Many read replicas can feed data from a small number of core servers, allowing for large, at scale workloads.
Improve Multisite Replication with Causal Clustering
Causal Clustering is a game changer for companies. If you want to implement this for your organization, you need to make sure your tools can scale and support it. Methodics IPLM is known to scale and support massive teams and dispersed workloads. It also is the only commercial platform with built-in support for Causal Clustering.
Methodics IPLM is trusted by 9 of the 10 top semiconductor companies to help ensure that design teams are able to efficient, while maintaining full traceability and IP security.
Connect with one of our IP experts to learn how Methodics can help you implement Causal Clustering and streamline your design process. You can get answers to your questions and gain access to evaluation resources to see how Methodics IPLM can benefit your business.
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