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Cloud Workload Resilience PulseMeter

Step 1 of 8

12%

How do you define cloud resiliency for cloud workloads? (Select 3)(Required)

The ability to recover from failures, high loads and cyberattacks.

Continue servicing workload requests during the recovery of failed components or services.

Implementing security measures to protect cloud workloads from cybersecurity threats like DDoS.

Maintaining uninterrupted service in the face of software, infrastructure and network failures or disruptions.

Designing cloud workloads to adapt to sudden changes in demand automatically.

Regularly performing backups to prevent data loss and enable quick recovery in case of failures.

Designing cloud workloads so they can more easily move between cloud locations and service providers.

Using geographically distributed or redundant cloud data centers.

Resiliency is just another marketing buzzword.

In what ways does cloud-native architecture improve the resiliency of workloads deployed in the cloud? (Rank order)

Smaller, self-contained microservices fail independently without impacting overall availability.
Containerized software provides isolation and consistency, making it easier to scale and recover from failure.
Stateless design patterns increase scalability and can fail independently without impacting other parts of cloud applications.
Serverless design pattern allows events to initiate the operation of the discrete functions as needed.
Cloud-native architecture significantly influences the resiliency of cloud-deployed applications.
Cloud-native architecture provides limited or no resiliency improvement.

How important is improving the resiliency of cloud workloads for your organization in 2024? (Select 1)(Required)

The number-one priority

In the top three priorities

In the top 10 priorities

Important but not a priority

Not important

Which of the following do you use to improve the resiliency of cloud workloads? (Select all that apply)(Required)

Containers

Microservices

Container orchestration

Serverless

Multiple cloud providers

Infrastructure-as-code (IaC)

Data distribution or replication

Observability tools based on OpenTelemetry

Failure testing

What factors in cloud-native (microservices) workloads increase resiliency? (Rank order)

Distribute workloads
Portable workloads across multiple cloud providers
Move some workloads to the edge
Kubernetes clusters for failover and load distribution
Stateless software design
Increased security posture
Setting meaningful and achievable resiliency goals

What are the most significant challenges to improving the resiliency of cloud workloads or cloud-native applications? (Select all that apply)(Required)

Lack of skills and knowledge

Legacy or existing architecture of applications

Large amount of technical debt

Multiple or conflicting definitions of resiliency

Inability to gain executive support

Ability to test resiliency without impacting service levels

Insufficient funding

Other

How much of your cloud workload is cloud-native today? (Select 1)(Required)

100% - all cloud-native

Greater than 50%

25-50%

Under 25%

0% - No cloud-native

What is your business or organization's size (# employees)? (Select 1)(Required)

1 - 100

101 - 500

501 - 1000

1001 - 5000

Over 5000