skip to main content
10.1145/3626111.3628206acmconferencesArticle/Chapter ViewAbstractPublication PagescommConference Proceedingsconference-collections
research-article

Simplifying Cloud Management with Cloudless Computing

Published: 28 November 2023 Publication History

Abstract

Cloud computing has transformed the IT industry, but managing cloud infrastructures remains a difficult task. We make a case for putting today's management practices, known as "Infrastructure-as-Code," on a firmer ground via a principled design. We call this end goal Cloudless Computing: it aims to simplify cloud infrastructure management tasks by supporting them "as-a-service," analogous to serverless computing that relieves users of the burden of managing server instances. By assisting tenants with these tasks, cloud resources will be presented to their users more readily without the undue burden of complex control. We describe the research problems by examining the typical lifecycle of today's cloud infrastructure management, and identify places where a cloudless approach will advance the state of the art.

References

[1]
26 cloud computing statistics, facts & trends for 2023. https://www.cloudwards.net/cloud-computing-statistics/#Sources.
[2]
AKS Autoscaler. https://learn.microsoft.com/en-us/azure/aks/cluster-autoscaler#about-the-cluster-autoscaler.
[3]
AWS Cloud Control API. https://aws.amazon.com/cloudcontrolapi/.
[4]
AWS CloudFormation. https://aws.amazon.com/cloudformation/.
[5]
AWS Lambda. https://aws.amazon.com/lambda/.
[6]
Azure Bicep. https://learn.microsoft.com/en-us/azure/azure-resource-manager/bicep/.
[7]
Azure Export for Terraform. https://github.com/Azure/aztfexport.
[8]
Azure Monitor Activity Log. https://learn.microsoft.com/en-us/azure/azure-monitor/essentials/activity-log.
[9]
Azure VM Scale Set. https://learn.microsoft.com/en-us/azure/virtual-machine-scale-sets/overview.
[10]
Checkov: ship code that's secure by default. https://bridgecrew.io/checkov/.
[11]
Comparing JSON and Bicep templates. https://learn.microsoft.com/en-us/azure/azure-resource-manager/bicep/compare-template-syntax.
[12]
Driftctl. https://driftctl.com/.
[13]
GCP Cloud Audit Logs. https://cloud.google.com/logging/docs/audit.
[14]
Hashicorp State-of-the-Cloud Survey. https://www.hashicorp.com/state-of-the-cloud.
[15]
HashiCorp Terraform on Azure. https://azure.microsoft.com/en-us/solutions/devops/terraform/.
[16]
HCL: the HashiCorp configuration language. https://github.com/hashicorp/hcl.
[17]
Infrastructure Drift and Drift Detection Explained. https://snyk.io/blog/infrastructure-drift-detection-mitigation/.
[18]
Opa's native query language rego. https://www.openpolicyagent.org/docs/latest/policy-language/.
[19]
Open Policy Agent. https://www.openpolicyagent.org/.
[20]
OpenTofu: The open source infrastructure as code tool. https://opentofu.org/.
[21]
Pulumi & Python. https://www.pulumi.com/docs/languages-sdks/python/.
[22]
[Pulumi] AI. https://www.pulumi.com/ai/.
[23]
[Pulumi] Automation API. https://www.pulumi.com/docs/using-pulumi/automation-api/.
[24]
Pulumi: Infrastructure as code in any programming language. https://www.pulumi.com/.
[25]
[Pulumi] Packages. https://www.pulumi.com/registry/.
[26]
[Pulumi] pulumi stack graph. https://www.pulumi.com/docs/cli/commands/pulumi_stack_graph/.
[27]
[Pulumi] Resource Providers. https://www.pulumi.com/docs/concepts/resources/providers/.
[28]
RightScale 2019 State of the Cloud Report from Flexera. https://resources.flexera.com/web/media/documents/rightscale-2019-state-of-the-cloud-report-from-flexera.pdf.
[29]
Sentinel integration with terraform. https://docs.hashicorp.com/sentinel/terraform.
[30]
STRUCTURA's AI Assistant. https://www.structura.io/resources/build-terraform-code-using-structuras-ai-assistant.
[31]
[styra] AI-Generated Infrastructure-as-Code: The Good, the Bad and the Ugly. https://www.styra.com/blog/ai-generated-infrastructure-as-code-the-good-the-bad-and-the-ugly/.
[32]
Terraform by Hashicorp. https://www.terraform.io/.
[33]
[Terraform] Command: apply. https://developer.hashicorp.com/terraform/cli/commands/apply.
[34]
[Terraform] Command: plan. https://developer.hashicorp.com/terraform/cli/commands/plan.
[35]
Terraform Locking. https://developer.hashicorp.com/terraform/language/state/locking.
[36]
[Terraform] Providers. https://registry.terraform.io/search/providers?namespace=hashicorp.
[37]
Terraform Registry Modules. https://registry.terraform.io/browse/modules.
[38]
Terraform: Resource Graph. https://developer.hashicorp.com/terraform/internals/graph.
[39]
Terraform Rollback. https://developers.cloudflare.com/terraform/tutorial/revert- configuration/.
[40]
Terraform validation. https://developer.hashicorp.com/terraform/cli/commands/validate.
[41]
Terraformer: CLI tool to generate terraform files from existing infrastructure. https://github.com/GoogleCloudPlatform/terraformer.
[42]
Terrascan: Detect compliance and security violations across Infrastructure as Code to mitigate risk before provisioning cloud native infrastructure. https://runterrascan.io/.
[43]
TFLint: A Pluggable Terraform Linter. https://github.com/terraform-linters/tflint.
[44]
TFSec: Security Scanner for Your Terraform Code. https://github.com/aquasecurity/tfsec.
[45]
Throttling Resource Manager requests. https://learn.microsoft.com/en- us/azure/azure-resource-manager/management/request- limits- and-throttling.
[46]
Tools for Infrastructure Drift Detection. https://snyk.io/blog/tools-infrastructure- drift- detection/.
[47]
T. Ahmed, S. Ghosh, C. Bansal, T. Zimmermann, X. Zhang, and S. Rajmohan. Recommending root-cause and mitigation steps for cloud incidents using large language models. In ICSE, 2023.
[48]
M. Artac, T. Borovssak, E. Di Nitto, M. Guerriero, and D. A. Tamburri. Devops: introducing infrastructure-as-code. In ICSE-C, 2017.
[49]
C. Barrett, C. L. Conway, M. Deters, L. Hadarean, D. Jovanović, T. King, A. Reynolds, and C. Tinelli. CVC4. In CAV, 2011.
[50]
B. Berabi, J. He, V. Raychev, and M. Vechev. Tfix: Learning to fix coding errors with a text-to-text transformer. In ICML, 2021.
[51]
S. Chasins, A. Cheung, N. Crooks, A. Ghodsi, K. Goldberg, J. E. Gonzalez, J. M. Hellerstein, M. I. Jordan, A. D. Joseph, M. W. Mahoney, A. Parameswaran, D. Patterson, R. A. Popa, K. Sen, S. Shenker, D. Song, and I. Stoica. The sky above the clouds, 2022.
[52]
M. Cusumano. Cloud computing and SaaS as new computing platforms. Communications of the ACM, 53(4):27--29, 2010.
[53]
L. De Moura and N. Bjørner. Z3: An efficient smt solver. In TACAS, 2008.
[54]
J. Eberhardt, S. Steffen, V. Raychev, and M. Vechev. Unsupervised learning of api aliasing specifications. In PLDI, 2019.
[55]
W. Fan, C. Hu, and C. Tian. Incremental graph computations: Doable and undoable. In SIGMOD, 2017.
[56]
B. Grubic, Y. Wang, T. Petrochko, R. Yaniv, B. Jones, D. Callies, M. Clarke-Lauer, D. Kelley, S. Demetriou, K. Yu, and C. Tang. Conveyor: One-tool-fits-all continuous software deployment at Meta. In OSDI, 2023.
[57]
Z. Guo, D. Cao, D. Tjong, J. Yang, C. Schlesinger, and N. Polikarpova. Type-directed program synthesis for restful apis. In PLDI, 2022.
[58]
J. He, C.-C. Lee, V. Raychev, and M. Vechev. Learning to find naming issues with big code and small supervision. In PLDI, 2021.
[59]
S. K. R. Kakarla, A. Tang, R. Beckett, K. Jayaraman, T. Millstein, Y. Tamir, and G. Varghese. Finding network misconfigurations by automatic template inference. In NSDI, 2020.
[60]
P. Lewis, E. Perez, A. Piktus, F. Petroni, V. Karpukhin, N. Goyal, H. Küttler, M. Lewis, W.-t. Yih, T. Rocktäschel, et al. Retrieval-augmented generation for knowledge-intensive nlp tasks. Advances in Neural Information Processing Systems, 33:9459--9474, 2020.
[61]
J. Li, B. Hui, G. Qu, B. Li, J. Yang, B. Li, B. Wang, B. Qin, R. Cao, R. Geng, et al. Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls. arXiv preprint, 2023.
[62]
Z. Li, Q. Cheng, K. Hsieh, Y. Dang, P. Huang, P. Singh, X. Yang, Q. Lin, Y. Wu, S. Levy, and M. Chintalapati. Gandalf: An intelligent, end-to-end analytics service for safe deployment in large-scale cloud infrastructure. In NSDI, 2020.
[63]
J. Lloyd. Cloud foundations and landing zones. In Infrastructure Leader's Guide to Google Cloud: Lead Your Organization's Google Cloud Adoption, Migration and Modernization Journey, pages 239--244. Springer, 2022.
[64]
T. Lorido-Botran, J. Miguel-Alonso, and J. A. Lozano. A review of auto-scaling techniques for elastic applications in cloud environments. Journal of grid computing, 12:559--592, 2014.
[65]
F. Petrillo, P. Merle, N. Moha, and Y.-G. Guéhéneuc. Are rest apis for cloud computing well-designed? an exploratory study. In ICSOC, 2016.
[66]
M. Santolucito, E. Zhai, R. Dhodapkar, A. Shim, and R. Piskac. Synthesizing configuration file specifications with association rule learning. In OOPSLA, 2017.
[67]
Z. Yin, X. Ma, J. Zheng, Y. Zhou, L. N. Bairavasundaram, and S. Pasupathy. An empirical study on configuration errors in commercial and open source systems. In SOSP, 2011.
[68]
T. Yu, Z. Li, Z. Zhang, R. Zhang, and D. Radev. Typesql: Knowledge-based type-aware neural text-to-sql generation. In NAACL, 2018.
[69]
E. Zhai, A. Chen, R. Piskac, M. Balakrishnan, B. Tian, B. Song, and H. Zhang. Check before you change: Preventing correlated failures in service updates. In NSDI, 2020.
[70]
J. Zhang, L. Renganarayana, X. Zhang, N. Ge, V. Bala, T. Xu, and Y. Zhou. Encore: Exploiting system environment and correlation information for misconfiguration detection. In ASPLOS, 2014.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
HotNets '23: Proceedings of the 22nd ACM Workshop on Hot Topics in Networks
November 2023
306 pages
ISBN:9798400704154
DOI:10.1145/3626111
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 November 2023

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Infrastructure as code
  2. cloud management

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Funding Sources

Conference

HotNets '23
Sponsor:
HotNets '23: The 22nd ACM Workshop on Hot Topics in Networks
November 28 - 29, 2023
MA, Cambridge, USA

Acceptance Rates

Overall Acceptance Rate 110 of 460 submissions, 24%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 218
    Total Downloads
  • Downloads (Last 12 months)137
  • Downloads (Last 6 weeks)8
Reflects downloads up to 17 Feb 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media