Currently,
power
management
network
server
operation
and
maintenance
tasks
are
primarily
manual,
resulting
in
a
substantial
workload
low
efficiency.
This
paper
conducts
an
in-depth
investigation
into
automation
technology
using
Ansible.
To
begin,
it
analyzes
the
existing
challenges
cluster
highlights
significance
of
automated
maintenance.
The
delves
Ansible
framework
array
extraction
method,
with
specific
focus
on
exploring
account
password
generation
modification
techniques.
enhance
response
speed
architecture,
this
incorporates
configuration
module
Intel
SGX
functionality.
Storing
remote
host
information
permanently,
as
utilized
by
Ansible,
significantly
reduces
time
enhances
security
login
information.
Experimental
test
results
demonstrate
that
proposed
approach
can
generate
highly
complex
controllable-length
passwords
effectively.
Moreover,
system's
is
noticeably
reduced,
confirming
efficacy
solution.
Infrastructure
as
Code
is
the
practice
of
developing
and
maintaining
computing
infrastructure
through
executable
source
code.
Unfortunately,
IaC
has
also
brought
about
new
cyber
attack
vectors.
Prior
work
therefore
proposed
static
analyses
that
detect
security
smells
in
files.
However,
they
have
so
far
remained
at
a
shallow
level,
disregarding
control
data
flow
scripts
under
analysis,
may
lack
awareness
specific
syntactic
constructs.
These
limitations
inhibit
quality
their
results.
To
address
these
limitations,
this
paper,
we
present
GASEL,
novel
smell
detector
for
Ansible
language.
It
uses
graph
queries
on
program
dependence
graphs
to
7
smells.
Our
evaluation
an
oracle
243
real-world
comparison
against
two
state-of-the-art
detectors
shows
syntax,
flow,
enables
our
approach
substantially
improve
both
precision
recall.
We
further
question
whether
additional
effort
required
develop
run
such
justified
practice.
end,
investigate
prevalence
indirection
across
more
than
15
000
scripts.
find
over
55%
contain
data-flow
indirection,
32%
require
whole-project
analysis
detect.
findings
motivate
need
deeper
tools
vulnerabilities
IaC.
Modern
Infrastructure
as
Code
(IaC)
programs
are
increasingly
complex
and
much
closer
to
traditional
software
than
simple
configuration
scripts.
Their
reliability
is
crucial
because
their
failure
prevents
the
deployment
of
applications,
incorrect
behavior
can
introduce
malfunction
severe
security
issues.
Yet,
engineering
tools
develop
reliable
programs,
such
testing
verification,
barely
used
in
IaC.
In
fact,
we
observed
that
developers
mainly
rely
on
integration
testing,
a
slow
expensive
practice
increase
confidence
end-to-end
functionality
but
infeasible
systematically
test
IaC
various
configurations—which
required
ensure
robustness.
On
other
hand,
fast
techniques,
unit
cumbersome
with
because,
today,
they
require
significant
coding
overhead
while
only
providing
limited
confidence.To
solve
this
issue,
envision
automated
tool
ProTI,
reducing
manual
boosting
results.
ProTI
embraces
modern
techniques
many
different
configurations.
Out
box,
fuzzer
for
Pulumi
TypeScript
randomly
program
configurations
termination,
correctness,
existing
policy
compliance.
Then
add
specifications
guide
random-based
value
generation,
additional
properties,
further
mocking,
making
property-based
tool.
Lastly,
aim
at
automatically
verifying
IaC-specific
e.g.,
access
paths
between
resources.
IEEE Transactions on Software Engineering,
Journal Year:
2024,
Volume and Issue:
50(6), P. 1585 - 1599
Published: May 1, 2024
Infrastructure
as
Code
(IaC)
enables
efficient
deployment
and
operation,
which
are
crucial
to
releasing
software
quickly.
As
setups
can
be
complex,
developers
implement
IaC
programs
in
general-purpose
programming
languages
like
TypeScript
Python,
using
PL-IaC
solutions
Pulumi
AWS
CDK.
The
reliability
of
such
is
even
more
relevant
than
traditional
because
a
bug
impacts
the
whole
system.
Yet,
though
testing
standard
development
practice,
it
rarely
used
for
programs.
For
instance,
August
2022,
less
1%
public
on
GitHub
implemented
tests.
Available
program
techniques
severely
limit
velocity
or
require
much
effort.
To
solve
these
issues,
we
propose
Automated
Configuration
Testing
(ACT),
methodology
test
many
configurations
quickly
with
low
ACT
automatically
mocks
all
resource
definitions
uses
generator
oracle
plugins
generation
validation.
We
ProTI,
tool
type-based
oracle,
support
application
specifications.
Our
evaluation
6
081
from
artificial
benchmarks
shows
that
ProTI
directly
applied
existing
programs,
finds
bugs
where
current
infeasible,
reusing
generators
oracles
thanks
its
pluggable
architecture.
In
the
dynamic
realm
of
HPC
(High-performance
computing)
and
cloud-native
applications,
ensuring
optimal
network
performance
for
Kubernetes
Container
Network
Interfaces
(CNIs)
is
critical.
Traditional
manual
methods
evaluating
bandwidth
latency
are
prone
to
errors,
time-consuming,
lack
consistency.
This
paper
introduces
a
novel
approach
that
leverages
Ansible
automate
coordinate
tests
across
diverse
CNIs,
profiles,
configurations.
By
automating
these
processes,
we
eliminate
potential
human
ensure
ability
replicate
process,
significantly
reduce
time
required
comprehensive
testing.
The
use
playbooks
facilitates
efficient
scalable
deployment,
configuration,
execution
tests,
enabling
standardized
benchmarking
various
environments.
set
playbooks,
which
will
make
available
online,
has
significant
real-world
impact
by
providing
DevOps
teams
with
robust
reliable
tools
consistently
monitoring
enhancing
performance.
This,
in
turn,
enhances
stability
efficiency
accelerates
development
cycle,
ensures
Kubernetes-based
infrastructures
can
meet
demanding
requirements
modern
applications.
Background.
Infrastructure-as-Code
(IaC)
is
an
emerging
practice
to
manage
cloud
infrastructure
resources
for
software
systems.
Modern
development
has
evolved
embrace
IaC
as
a
best
consistently
provisioning
and
managing
using
various
tools
such
Terraform
Ansible.
However,
recent
studies
highlighted
that
developers
still
encounter
challenges
with
tools.
Aims.
We
aim
in
this
paper
understand
the
different
analyze
trend
of
seeking
assistance
on
Q&A
platforms
context
IaC.
To
end,
we
conduct
large-scale
empirical
study
investigating
developers'
discussions
Stack
Overflow.
Method.
first
collect
IaC-relevant
tags
Overflow,
constituting
dataset
comprises
52,692
questions
64,078
answers.
Then,
group
into
specific
topics
Latent
Dirichlet
Allocation
(LDA)
method,
which
optimize
Genetic
Algorithm
(GA)
parameter's
fine-tuning.
Finally,
gain
better
insights,
identified
based
criteria
popularity
difficulty.
Results.
Our
findings
reveal
average
yearly
increase
150%
terms
IaC-related
135%
users
between
2011
2022.
Furthermore,
observe
revolve
around
seven
main
topics:
server
configuration,
policy
networking,
deployment
pipelines,
variable
management,
templating,
file
management.
Notably,
found
configuration
management
are
most
popular
topics,
i.e.,
discussed
among
developers,
while
pipelines
templating
difficult.
Conclusions.
results
shed
light
often
encountered
by
platforms.
These
important
implications
practitioners
support
real-world
settings
researchers
community
needs
further
investigate
aspects.
