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Lambda infrastructure automation
AWS Lambda Managed Instances Offer Specialized Compute Configurations
AWS Lambda Managed Instances bring Lambda’s operational simplicity to EC2, enabling specialized compute options, cost efficiency, and predictable scaling ...
Adrian Bridgwater
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December 10, 2025
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aws
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AWS cloud engineering tools
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AWS compute services
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AWS Graviton4
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AWS Lambda
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AWS Lambda Managed Instances
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AWS operational simplicity
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cloud cost optimization
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cloud native
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cloud scalability
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cloud services
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compute-optimized instances
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developers
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EC2 specialized compute
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GPU accelerated computing
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Lambda compute configurations
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Lambda infrastructure automation
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Lambda steady-state workloads
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memory-optimized instances
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parallel request processing
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pay-per-use compute
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serverless compute
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serverless vs EC2
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storage-optimized instances
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VPC configuration Lambda
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Modern Software Development and Delivery
1
Q1
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Q2
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Q3
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Q4
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Q5
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Q6
How would you best describe your organization's current software delivery environment(s) on mainframe computers? (Select all that apply)
(Required)
Primarily manual or legacy delivery processes
Automated CI/CD in limited areas
Hybrid environment with multiple delivery platforms and toolchains
Mostly standardized CI/CD platform
Intelligent, governed software delivery platform
My organization does not utilize mainframes
Not sure / don't know
Which outcomes are most important to your organization's software delivery strategy today? (Select up to three)
(Required)
Accelerating software delivery
Automating build, test, and deployment workflows
Integrating security and compliance into delivery
Providing governance and auditability
Supporting AI-assisted software delivery
Improving software supply chain visibility
Standardizing delivery across teams
Supporting both modern and legacy application delivery
Other
Not sure / don't know
What, if anything, is limiting your organization's mainframe software delivery progress? (Select up to three)
(Required)
Legacy applications or legacy development processes
Fragmented tools and disconnected workflows
Security, governance, or compliance requirements
Limited automation across the delivery lifecycle
Difficulty integrating AI into software delivery workflows
Skills or resource constraints
Organizational or cultural resistance to change
Limited visibility across the software delivery lifecycle
Budget or investment constraints
Other
Nothing is significantly limiting our progress
Not sure / don't know
In which areas of your mainframe software delivery environment are you currently using AI? (Select all that apply)
(Required)
Code generation / developer assistance
Automated testing / test generation
Build and pipeline optimization
Deployment automation
Monitoring and incident response
Security / compliance automation
Other
We are not currently using AI in our environment today
As software delivery responsibilities expand beyond traditional build, test, and deploy, which of the following areas is the most challenging for your organization today with respect to mainframe software delivery? (Select one)
(Required)
Integrating security throughout the software delivery lifecycle
Meeting governance, audit, or compliance requirements
Managing software supply chain integrity and visibility
Operationalizing AI across software delivery workflows
Coordinating software delivery across diverse tools, teams, and environments
Other
None of these are significant challenges
Not sure / don't know
Which of the following do you expect is most likely to accelerate your organization's mainframe software delivery progress over the next 12-18 months? (Select one)
(Required)
Greater automation across the software delivery lifecycle
Broader use of AI-assisted software delivery workflows
Stronger governance, policy, and compliance automation
Improved software supply chain visibility
Better integration across software delivery tools and platforms
Greater standardization across development teams
Other
No significant changes are planned
Not sure / don't know
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