diff --git a/CLAUDE.md b/CLAUDE.md
new file mode 100644
index 0000000..4700c64
--- /dev/null
+++ b/CLAUDE.md
@@ -0,0 +1,25 @@
+# API-TO-DATAFRAME DEVELOPMENT GUIDE
+
+## Build & Test Commands
+- Setup: `poetry install`
+- Run all tests: `poetry run pytest`
+- Run single test: `poetry run pytest tests/test_file.py::test_function`
+- Coverage: `poetry run coverage run -m pytest && poetry run coverage report`
+- Lint: `poetry run pylint src/`
+- Format: `poetry run black src/ tests/`
+
+## Code Style Guidelines
+- Use Python 3.9+ features
+- Import order: stdlib → third-party → local
+- Type hints required for function parameters and return values
+- Follow black formatting (max line length 88)
+- Variable naming: snake_case for variables/functions, PascalCase for classes
+- Error handling: use try/except with specific exceptions, log errors
+- Use f-strings for string formatting
+- Test coverage target: 90%+
+- Use dataclasses or typed dictionaries for structured data
+
+## Architecture
+- MVC-like pattern: controllers, models, utils
+- Core functionality in models package
+- Client interactions in controller package
\ No newline at end of file
diff --git a/poetry.lock b/poetry.lock
index 3b3a1eb..01da2e1 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,29 +1,16 @@
 # This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand.
 
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-
 [[package]]
 name = "astroid"
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 description = "An abstract syntax tree for Python with inference support."
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 markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
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 ]
 
 [package.dependencies]
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 [[package]]
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 version = "24.2"
 description = "Core utilities for Python packages"
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 [package.dependencies]
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 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -1162,175 +802,17 @@ tomlkit = ">=0.4"
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 plugin = ["poetry (>=1.2.0)"]
 
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-
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-version = "3.3.4"
+version = "3.3.5"
 description = "python code static checker"
 optional = false
 python-versions = ">=3.9.0"
 groups = ["dev"]
 markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
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@@ -1338,8 +820,8 @@ astroid = ">=3.3.8,<=3.4.0-dev0"
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+version = "0.25.7"
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 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
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 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]
 
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-]
-
-[[package]]
-name = "zipp"
-version = "3.21.0"
-description = "Backport of pathlib-compatible object wrapper for zip files"
-optional = false
-python-versions = ">=3.9"
-groups = ["main"]
-markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
-files = [
-    {file = "zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931"},
-    {file = "zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4"},
-]
-
-[package.extras]
-check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
-cover = ["pytest-cov"]
-doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-enabler = ["pytest-enabler (>=2.2)"]
-test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
-type = ["pytest-mypy"]
-
 [metadata]
 lock-version = "2.1"
 python-versions = "^3.9"
-content-hash = "3d83bf2a4a90cc66113263e3b85c761cd9d24aeaadcb7e179f945c65bbf8ef24"
+content-hash = "ac39d671b1de63ed2eaf0c862168197e8bf9b639a134d1c0118f1535edb90d35"
diff --git a/pyproject.toml b/pyproject.toml
index f76f668..c8998dc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "api-to-dataframe"
-version = "1.5.2"
+version = "2.0.0"
 description = "A package to convert API responses to pandas dataframe"
 authors = ["IvanildoBarauna <ivanildo.jnr@outlook.com>"]
 readme = "README.md"
@@ -27,7 +27,6 @@ python = "^3.9"
 pandas = "^2.2.3"
 requests = "^2.32.3"
 logging = "^0.4.9.6"
-otel-wrapper = "^0.1.1"
 
 [tool.poetry.group.dev.dependencies]
 poetry-dynamic-versioning = "^1.3.0"
diff --git a/src/api_to_dataframe/controller/client_builder.py b/src/api_to_dataframe/controller/client_builder.py
index 851898f..107b453 100644
--- a/src/api_to_dataframe/controller/client_builder.py
+++ b/src/api_to_dataframe/controller/client_builder.py
@@ -1,7 +1,6 @@
 from api_to_dataframe.models.retainer import retry_strategies, Strategies
 from api_to_dataframe.models.get_data import GetData
-from api_to_dataframe.utils.logger import logger, telemetry
-import time
+from api_to_dataframe.utils.logger import logger
 
 
 class ClientBuilder:
@@ -37,38 +36,18 @@ def __init__(  # pylint: disable=too-many-positional-arguments,too-many-argument
         if endpoint == "":
             error_msg = "endpoint cannot be an empty string"
             logger.error(error_msg)
-            telemetry.logs().new_log(
-                msg=error_msg,
-                tags={"component": "ClientBuilder", "method": "__init__"},
-                level=40  # ERROR level
-            )
             raise ValueError
         if not isinstance(retries, int) or retries < 0:
             error_msg = "retries must be a non-negative integer"
             logger.error(error_msg)
-            telemetry.logs().new_log(
-                msg=error_msg,
-                tags={"component": "ClientBuilder", "method": "__init__"},
-                level=40  # ERROR level
-            )
             raise ValueError
         if not isinstance(initial_delay, int) or initial_delay < 0:
             error_msg = "initial_delay must be a non-negative integer"
             logger.error(error_msg)
-            telemetry.logs().new_log(
-                msg=error_msg,
-                tags={"component": "ClientBuilder", "method": "__init__"},
-                level=40  # ERROR level
-            )
             raise ValueError
         if not isinstance(connection_timeout, int) or connection_timeout < 0:
             error_msg = "connection_timeout must be a non-negative integer"
             logger.error(error_msg)
-            telemetry.logs().new_log(
-                msg=error_msg,
-                tags={"component": "ClientBuilder", "method": "__init__"},
-                level=40  # ERROR level
-            )
             raise ValueError
 
         self.endpoint = endpoint
@@ -78,28 +57,6 @@ def __init__(  # pylint: disable=too-many-positional-arguments,too-many-argument
         self.retries = retries
         self.delay = initial_delay
 
-        # Record client initialization metric
-        telemetry.metrics().metric_increment(
-            name="client.initialization",
-            tags={
-                "endpoint": endpoint,
-                "retry_strategy": retry_strategy.name,
-                "connection_timeout": str(connection_timeout)
-            }
-        )
-
-        # Log initialization
-        telemetry.logs().new_log(
-            msg=f"ClientBuilder initialized with endpoint {endpoint}",
-            tags={
-                "endpoint": endpoint,
-                "retry_strategy": retry_strategy.name,
-                "connection_timeout": str(connection_timeout),
-                "component": "ClientBuilder"
-            },
-            level=20  # INFO level
-        )
-
     @retry_strategies
     def get_api_data(self):
         """
@@ -112,67 +69,13 @@ def get_api_data(self):
         Returns:
             dict: The JSON response from the API as a dictionary.
         """
-        # Use the telemetry spans with new API
-        span = telemetry.traces().new_span("get_api_data")
-        try:
-            # Add span attributes
-            span.set_attribute("endpoint", self.endpoint)
-            span.set_attribute("retry_strategy", self.retry_strategy.name)
-            span.set_attribute("connection_timeout", self.connection_timeout)
-
-            # Log the API request
-            telemetry.logs().new_log(
-                msg=f"Making API request to {self.endpoint}",
-                tags={
-                    "endpoint": self.endpoint,
-                    "component": "ClientBuilder",
-                    "method": "get_api_data"
-                },
-                level=20  # INFO level
-            )
-
-            # Record the start time for response time measurement
-            start_time = time.time()
-
-            # Make the API request
-            response = GetData.get_response(
-                endpoint=self.endpoint,
-                headers=self.headers,
-                connection_timeout=self.connection_timeout,
-            )
-
-            # Calculate response time
-            response_time = time.time() - start_time
-
-            # Record response time as histogram
-            telemetry.metrics().record_histogram(
-                name="api.response_time",
-                tags={"endpoint": self.endpoint},
-                value=response_time
-            )
-
-            # Record successful request metric
-            telemetry.metrics().metric_increment(
-                name="api.request.success",
-                tags={"endpoint": self.endpoint}
-            )
-
-            # Log success
-            telemetry.logs().new_log(
-                msg=f"API request to {self.endpoint} successful",
-                tags={
-                    "endpoint": self.endpoint,
-                    "response_status": response.status_code,
-                    "response_time": response_time,
-                    "component": "ClientBuilder",
-                    "method": "get_api_data"
-                },
-                level=20  # INFO level
-            )
+        response = GetData.get_response(
+            endpoint=self.endpoint,
+            headers=self.headers,
+            connection_timeout=self.connection_timeout,
+        )
 
-            return response.json()
-        finally:
-            span.end()
+        return response.json()
 
     @staticmethod
     def api_to_dataframe(response: dict):
@@ -189,69 +92,4 @@ def api_to_dataframe(response: dict):
         Returns:
             DataFrame: A pandas DataFrame containing the data from the API response.
         """
-        # Use telemetry with new API
-        span = telemetry.traces().new_span("api_to_dataframe")
-        try:
-            response_size = len(response) if isinstance(response, list) else 1
-            span.set_attribute("response_size", response_size)
-
-            # Log conversion start
-            telemetry.logs().new_log(
-                msg="Converting API response to DataFrame",
-                tags={
-                    "response_size": response_size,
-                    "response_type": type(response).__name__,
-                    "component": "ClientBuilder",
-                    "method": "api_to_dataframe"
-                },
-                level=20  # INFO level
-            )
-
-            try:
-                # Convert to dataframe
-                df = GetData.to_dataframe(response)
-
-                # Record metrics
-                telemetry.metrics().metric_increment(
-                    name="dataframe.conversion.success",
-                    tags={"size": len(df)}
-                )
-
-                # Log success
-                telemetry.logs().new_log(
-                    msg="Successfully converted API response to DataFrame",
-                    tags={
-                        "dataframe_rows": len(df),
-                        "dataframe_columns": len(df.columns),
-                        "component": "ClientBuilder",
-                        "method": "api_to_dataframe"
-                    },
-                    level=20  # INFO level
-                )
-
-                return df
-
-            except Exception as e:
-                # Record failure metric
-                telemetry.metrics().metric_increment(
-                    name="dataframe.conversion.failure",
-                    tags={"error_type": type(e).__name__}
-                )
-
-                # Log error
-                error_msg = f"Failed to convert API response to DataFrame: {str(e)}"
-                telemetry.logs().new_log(
-                    msg=error_msg,
-                    tags={
-                        "error": str(e),
-                        "error_type": type(e).__name__,
-                        "component": "ClientBuilder",
-                        "method": "api_to_dataframe"
-                    },
-                    level=40  # ERROR level
-                )
-
-                # Re-raise the exception
-                raise
-        finally:
-            span.end()
+        return GetData.to_dataframe(response)
diff --git a/src/api_to_dataframe/models/get_data.py b/src/api_to_dataframe/models/get_data.py
index 449b1f8..a61cacc 100644
--- a/src/api_to_dataframe/models/get_data.py
+++ b/src/api_to_dataframe/models/get_data.py
@@ -1,221 +1,27 @@
 import requests
 import pandas as pd
-from api_to_dataframe.utils.logger import logger, telemetry
+from api_to_dataframe.utils.logger import logger
 
 
 class GetData:
     @staticmethod
     def get_response(endpoint: str, headers: dict, connection_timeout: int):
-        # Start a span for the API request
-        span = telemetry.traces().new_span("http_request")
-        try:
-            span.set_attribute("http.url", endpoint)
-            span.set_attribute("http.method", "GET")
-            span.set_attribute("http.timeout", connection_timeout)
+        # Make the request
+        response = requests.get(endpoint, timeout=connection_timeout, headers=headers)
 
-            # Log the request
-            telemetry.logs().new_log(
-                msg=f"Sending HTTP GET request to {endpoint}",
-                tags={
-                    "endpoint": endpoint,
-                    "timeout": connection_timeout,
-                    "component": "GetData",
-                    "method": "get_response"
-                },
-                level=20  # INFO level
-            )
+        # Attempt to raise for status to catch errors
+        response.raise_for_status()
 
-            try:
-                # Make the request
-                response = requests.get(endpoint, timeout=connection_timeout, headers=headers)
-
-                # Set response attributes on span
-                span.set_attribute("http.status_code", response.status_code)
-                span.set_attribute("http.response_content_length", len(response.content))
-
-                # Attempt to raise for status to catch errors
-                response.raise_for_status()
-
-                # Log successful response
-                telemetry.logs().new_log(
-                    msg=f"Received HTTP {response.status_code} response from {endpoint}",
-                    tags={
-                        "endpoint": endpoint,
-                        "status_code": response.status_code,
-                        "response_size": len(response.content),
-                        "component": "GetData",
-                        "method": "get_response"
-                    },
-                    level=20  # INFO level
-                )
-
-                # Record successful request metric
-                telemetry.metrics().metric_increment(
-                    name="http.request.success",
-                    tags={
-                        "endpoint": endpoint,
-                        "status_code": response.status_code
-                    }
-                )
-
-                return response
-
-            except requests.exceptions.RequestException as e:
-                # Record the exception on the span
-                span.record_exception(e)
-                span.set_attribute("error", True)
-                span.set_attribute("error.type", type(e).__name__)
-                span.set_attribute("error.message", str(e))
-
-                # Log the error
-                telemetry.logs().new_log(
-                    msg=f"HTTP request failed: {str(e)}",
-                    tags={
-                        "endpoint": endpoint,
-                        "error": str(e),
-                        "error_type": type(e).__name__,
-                        "component": "GetData",
-                        "method": "get_response"
-                    },
-                    level=40  # ERROR level
-                )
-
-                # Record failure metric
-                telemetry.metrics().metric_increment(
-                    name="http.request.failure",
-                    tags={
-                        "endpoint": endpoint,
-                        "error_type": type(e).__name__
-                    }
-                )
-
-                # Re-raise the exception
-                raise
-        finally:
-            span.end()
+        return response
 
     @staticmethod
     def to_dataframe(response):
-        # Start a span for dataframe conversion
-        span = telemetry.traces().new_span("convert_to_dataframe")
-        try:
-            # Set attributes about the data
-            data_size = len(response) if isinstance(response, list) else 1
-            span.set_attribute("data.size", data_size)
-            span.set_attribute("data.type", type(response).__name__)
-
-            # Log conversion attempt
-            telemetry.logs().new_log(
-                msg="Converting data to DataFrame",
-                tags={
-                    "data_size": data_size,
-                    "data_type": type(response).__name__,
-                    "component": "GetData",
-                    "method": "to_dataframe"
-                },
-                level=20  # INFO level
-            )
-
-            try:
-                # Convert to DataFrame
-                df = pd.DataFrame(response)
-
-                # Check if DataFrame is empty
-                if df.empty:
-                    error_msg = "::: DataFrame is empty :::"
-                    logger.error(error_msg)
-
-                    # Log the error with OpenTelemetry
-                    telemetry.logs().new_log(
-                        msg=error_msg,
-                        tags={
-                            "data_size": data_size,
-                            "data_type": type(response).__name__,
-                            "component": "GetData",
-                            "method": "to_dataframe"
-                        },
-                        level=40  # ERROR level
-                    )
-
-                    # Record empty DataFrame metric
-                    telemetry.metrics().metric_increment(
-                        name="dataframe.empty",
-                        tags={"data_type": type(response).__name__}
-                    )
-
-                    # Set span as error
-                    span.set_attribute("error", True)
-                    span.set_attribute("error.type", "ValueError")
-                    span.set_attribute("error.message", error_msg)
-
-                    raise ValueError(error_msg)
-
-                # Log success
-                telemetry.logs().new_log(
-                    msg="Successfully converted data to DataFrame",
-                    tags={
-                        "rows": len(df),
-                        "columns": len(df.columns),
-                        "component": "GetData",
-                        "method": "to_dataframe"
-                    },
-                    level=20  # INFO level
-                )
-
-                # Record dataframe metrics
-                telemetry.metrics().record_gauge(
-                    name="dataframe.rows",
-                    tags={"data_type": type(response).__name__},
-                    value=float(len(df))
-                )
-
-                telemetry.metrics().record_gauge(
-                    name="dataframe.columns",
-                    tags={"data_type": type(response).__name__},
-                    value=float(len(df.columns))
-                )
-
-                # Set additional span attributes
-                span.set_attribute("dataframe.rows", len(df))
-                span.set_attribute("dataframe.columns", len(df.columns))
-
-                return df
-
-            except ValueError:
-                # Re-raise ValueErrors (like empty DataFrame)
-                raise
-
-            except Exception as err:
-                # Log the error
-                error_msg = f"Invalid response for transform in dataframe: {err}"
-                logger.error(error_msg)
-
-                # Log with OpenTelemetry
-                telemetry.logs().new_log(
-                    msg=error_msg,
-                    tags={
-                        "error": str(err),
-                        "error_type": type(err).__name__,
-                        "data_type": type(response).__name__,
-                        "component": "GetData",
-                        "method": "to_dataframe"
-                    },
-                    level=40  # ERROR level
-                )
-
-                # Record conversion failure metric
-                telemetry.metrics().metric_increment(
-                    name="dataframe.conversion.error",
-                    tags={"error_type": type(err).__name__}
-                )
+        df = pd.DataFrame(response)
 
-                # Record the exception on the span
-                span.record_exception(err)
-                span.set_attribute("error", True)
-                span.set_attribute("error.type", type(err).__name__)
-                span.set_attribute("error.message", str(err))
+        # Check if DataFrame is empty
+        if df.empty:
+            error_msg = "::: DataFrame is empty :::"
+            logger.error(error_msg)
+            raise ValueError(error_msg)
 
-                # Raise TypeError with original error as cause
-                raise TypeError(error_msg) from err
-        finally:
-            span.end()
+        return df
diff --git a/src/api_to_dataframe/models/retainer.py b/src/api_to_dataframe/models/retainer.py
index bf7139c..e69b25b 100644
--- a/src/api_to_dataframe/models/retainer.py
+++ b/src/api_to_dataframe/models/retainer.py
@@ -2,7 +2,7 @@
 from enum import Enum
 
 from requests.exceptions import RequestException
-from api_to_dataframe.utils.logger import logger, telemetry
+from api_to_dataframe.utils.logger import logger
 from api_to_dataframe.utils import Constants
 
 
@@ -15,177 +15,25 @@ class Strategies(Enum):
 def retry_strategies(func):
     def wrapper(*args, **kwargs):  # pylint: disable=inconsistent-return-statements
         retry_number = 0
-
-        # Get the endpoint for better observability context
-        endpoint = args[0].endpoint if hasattr(args[0], 'endpoint') else 'unknown'
-
-        # Start a span for this entire retry operation
-        span = telemetry.traces().new_span("retry_operation")
-        try:
-            span.set_attribute("endpoint", endpoint)
-            span.set_attribute("retry_strategy", args[0].retry_strategy.name)
-            span.set_attribute("max_retries", args[0].retries)
-
-            while retry_number < args[0].retries:
-                try:
-                    # Log retry attempt if not the first attempt
-                    if retry_number > 0:
-                        # Log using traditional logger
-                        logger.info(f"Trying for the {retry_number} of {Constants.MAX_OF_RETRIES} retries. Using {args[0].retry_strategy}")
-
-                        # Log using OpenTelemetry
-                        telemetry.logs().new_log(
-                            msg=f"Retry attempt {retry_number} of {args[0].retries}",
-                            tags={
-                                "endpoint": endpoint,
-                                "retry_number": retry_number,
-                                "max_retries": args[0].retries,
-                                "retry_strategy": args[0].retry_strategy.name,
-                                "component": "RetryStrategy"
-                            },
-                            level=20  # INFO level
-                        )
-
-                        # Record retry metric
-                        telemetry.metrics().metric_increment(
-                            name="api.request.retry",
-                            tags={
-                                "endpoint": endpoint,
-                                "retry_strategy": args[0].retry_strategy.name
-                            }
-                        )
-
-                        # Update span with current retry count
-                        span.set_attribute("current_retry", retry_number)
-
-                    # Execute the wrapped function
-                    result = func(*args, **kwargs)
-
-                    # If we got here, it succeeded - record success metric after retries
-                    if retry_number > 0:
-                        telemetry.metrics().metric_increment(
-                            name="api.request.retry.success",
-                            tags={
-                                "endpoint": endpoint,
-                                "retry_count": retry_number,
-                                "retry_strategy": args[0].retry_strategy.name
-                            }
-                        )
-
-                        telemetry.logs().new_log(
-                            msg=f"Request succeeded after {retry_number} retries",
-                            tags={
-                                "endpoint": endpoint,
-                                "retry_count": retry_number,
-                                "retry_strategy": args[0].retry_strategy.name,
-                                "component": "RetryStrategy"
-                            },
-                            level=20  # INFO level
-                        )
-
-                    return result
-
-                except RequestException as e:
-                    retry_number += 1
-
-                    # Record exception in the span
-                    span.record_exception(e)
-                    span.set_attribute("failed_attempt", retry_number)
-
-                    # Handle different retry strategies
-                    if args[0].retry_strategy == Strategies.NO_RETRY_STRATEGY:
-                        # Log failure with OpenTelemetry
-                        telemetry.logs().new_log(
-                            msg=f"Request failed with {type(e).__name__}, no retry strategy configured",
-                            tags={
-                                "endpoint": endpoint,
-                                "error": str(e),
-                                "error_type": type(e).__name__,
-                                "component": "RetryStrategy"
-                            },
-                            level=40  # ERROR level
-                        )
-
-                        # Record failure metric
-                        telemetry.metrics().metric_increment(
-                            name="api.request.failure",
-                            tags={
-                                "endpoint": endpoint,
-                                "error_type": type(e).__name__,
-                                "retry_strategy": "none"
-                            }
-                        )
-
-                        raise e
-
-                    # Apply delay based on strategy
-                    if args[0].retry_strategy == Strategies.LINEAR_RETRY_STRATEGY:
-                        delay = args[0].delay
-                        strategy_name = "linear"
-                    elif args[0].retry_strategy == Strategies.EXPONENTIAL_RETRY_STRATEGY:
-                        delay = args[0].delay * retry_number
-                        strategy_name = "exponential"
-
-                    # Log retry delay
-                    telemetry.logs().new_log(
-                        msg=f"Request failed, retrying in {delay}s (strategy: {strategy_name})",
-                        tags={
-                            "endpoint": endpoint,
-                            "retry_count": retry_number,
-                            "delay": delay,
-                            "strategy": strategy_name,
-                            "error": str(e),
-                            "error_type": type(e).__name__,
-                            "component": "RetryStrategy"
-                        },
-                        level=30  # WARNING level
-                    )
-
-                    # Record the delay time in metrics
-                    telemetry.metrics().record_gauge(
-                        name="api.retry.delay",
-                        tags={
-                            "endpoint": endpoint,
-                            "retry_count": retry_number,
-                            "strategy": strategy_name
-                        },
-                        value=float(delay)
+        while retry_number < args[0].retries:
+            try:
+                if retry_number > 0:
+                    logger.info(
+                        f"Trying for the {retry_number} of {Constants.MAX_OF_RETRIES} retries. Using {args[0].retry_strategy}"
                     )
-
-                    # Sleep for the calculated delay
-                    time.sleep(delay)
-
-                    # Check if we've reached max retries
-                    if retry_number in (args[0].retries, Constants.MAX_OF_RETRIES):
-                        # Log final failure
-                        error_msg = f"Failed after {retry_number} retries"
-                        logger.error(error_msg)
-
-                        telemetry.logs().new_log(
-                            msg=error_msg,
-                            tags={
-                                "endpoint": endpoint,
-                                "retry_count": retry_number,
-                                "max_retries": args[0].retries,
-                                "error": str(e),
-                                "error_type": type(e).__name__,
-                                "component": "RetryStrategy"
-                            },
-                            level=40  # ERROR level
-                        )
-
-                        # Record final failure metric
-                        telemetry.metrics().metric_increment(
-                            name="api.request.retry.exhausted",
-                            tags={
-                                "endpoint": endpoint,
-                                "retry_strategy": args[0].retry_strategy.name,
-                                "error_type": type(e).__name__
-                            }
-                        )
-
-                        raise e
-        finally:
-            span.end()
+                return func(*args, **kwargs)
+            except RequestException as e:
+                retry_number += 1
+
+                if args[0].retry_strategy == Strategies.NO_RETRY_STRATEGY:
+                    raise e
+                if args[0].retry_strategy == Strategies.LINEAR_RETRY_STRATEGY:
+                    time.sleep(args[0].delay)
+                elif args[0].retry_strategy == Strategies.EXPONENTIAL_RETRY_STRATEGY:
+                    time.sleep(args[0].delay * retry_number)
+
+                if retry_number in (args[0].retries, Constants.MAX_OF_RETRIES):
+                    logger.error(f"Failed after {retry_number} retries")
+                    raise e
 
     return wrapper
diff --git a/src/api_to_dataframe/utils/logger.py b/src/api_to_dataframe/utils/logger.py
index 56f17bb..a5abe3c 100644
--- a/src/api_to_dataframe/utils/logger.py
+++ b/src/api_to_dataframe/utils/logger.py
@@ -1,7 +1,5 @@
 import logging
-from otel_wrapper.deps_injector import wrapper_builder
 
-# Configure logging once at the start of your program
 logging.basicConfig(
     encoding="utf-8",
     format="%(asctime)s :: api-to-dataframe[%(levelname)s] :: %(message)s",
@@ -11,6 +9,3 @@
 
 # Initialize traditional logger
 logger = logging.getLogger("api-to-dataframe")
-
-# Initialize OpenTelemetry wrapper
-telemetry = wrapper_builder("api-to-dataframe")
\ No newline at end of file
diff --git a/tests/conftest.py b/tests/conftest.py
deleted file mode 100644
index a4e3245..0000000
--- a/tests/conftest.py
+++ /dev/null
@@ -1,57 +0,0 @@
-import pytest
-import logging
-import contextlib
-from unittest.mock import patch, MagicMock
-
-# Create a simple context manager to replace span_in_context
-@contextlib.contextmanager
-def mock_span_in_context(name, kind=None, attributes=None):
-    mock_span = MagicMock()
-    mock_context = MagicMock()
-    yield (mock_span, mock_context)
-
-@pytest.fixture(autouse=True)
-def patch_otel_for_tests(monkeypatch):
-    """
-    Completely disable and replace OpenTelemetry to prevent test failures.
-    This is a more aggressive approach that should work even with coverage.
-    """
-    # Create a proper logger with a handler that won't cause errors
-    test_logger = logging.getLogger("test-logger")
-    test_logger.setLevel(logging.INFO)
-    handler = logging.NullHandler()
-    handler.setLevel(logging.INFO)
-    test_logger.addHandler(handler)
-    test_logger.propagate = False
-    
-    # Mock telemetry components
-    mock_traces = MagicMock()
-    mock_traces.span_in_context.side_effect = mock_span_in_context
-    mock_traces.get_tracer.return_value = MagicMock()
-    mock_traces.new_span.return_value = MagicMock()
-    
-    mock_logs = MagicMock()
-    mock_logs.new_log.return_value = None
-    mock_logs.get_logger.return_value = test_logger
-    
-    mock_metrics = MagicMock()
-    mock_metrics.metric_increment.return_value = None
-    mock_metrics.record_gauge.return_value = None
-    mock_metrics.record_histogram.return_value = None
-    
-    # Mock main telemetry object
-    mock_telemetry = MagicMock()
-    mock_telemetry.traces.return_value = mock_traces
-    mock_telemetry.logs.return_value = mock_logs
-    mock_telemetry.metrics.return_value = mock_metrics
-    
-    # Apply all patches
-    monkeypatch.setattr("api_to_dataframe.utils.logger.telemetry", mock_telemetry)
-    monkeypatch.setattr("api_to_dataframe.utils.logger.logger", test_logger)
-    monkeypatch.setattr("api_to_dataframe.models.retainer.logger", test_logger)
-    monkeypatch.setattr("api_to_dataframe.models.retainer.telemetry", mock_telemetry)
-    monkeypatch.setattr("api_to_dataframe.controller.client_builder.telemetry", mock_telemetry)
-    monkeypatch.setattr("api_to_dataframe.models.get_data.telemetry", mock_telemetry)
-    
-    # Also patch the wrapper_builder function in case it's used directly
-    monkeypatch.setattr("otel_wrapper.deps_injector.wrapper_builder", lambda app_name: mock_telemetry)
\ No newline at end of file
diff --git a/tests/test_controller_client_builder.py b/tests/test_controller_client_builder.py
index 5628b7a..8af9bf5 100644
--- a/tests/test_controller_client_builder.py
+++ b/tests/test_controller_client_builder.py
@@ -1,7 +1,8 @@
 import pytest
 import pandas as pd
+import responses
 
-from api_to_dataframe import ClientBuilder
+from api_to_dataframe import ClientBuilder, RetryStrategies
 
 
 @pytest.fixture()
@@ -63,6 +64,29 @@ def test_constructor_with_param(client_setup):  # pylint: disable=redefined-oute
     assert new_client.endpoint == expected_result
 
 
+def test_constructor_with_headers():
+    """Test ClientBuilder with custom headers"""
+    custom_headers = {"Authorization": "Bearer token123", "Content-Type": "application/json"}
+    client = ClientBuilder(
+        endpoint="https://economia.awesomeapi.com.br/last/USD-BRL",
+        headers=custom_headers
+    )
+    assert client.headers == custom_headers
+
+
+def test_constructor_with_retry_strategy():
+    """Test ClientBuilder with different retry strategies"""
+    client = ClientBuilder(
+        endpoint="https://economia.awesomeapi.com.br/last/USD-BRL",
+        retry_strategy=RetryStrategies.LINEAR_RETRY_STRATEGY,
+        retries=5,
+        initial_delay=2
+    )
+    assert client.retry_strategy == RetryStrategies.LINEAR_RETRY_STRATEGY
+    assert client.retries == 5
+    assert client.delay == 2
+
+
 def test_response_to_json(client_setup):  # pylint: disable=redefined-outer-name
     new_client = client_setup
     response = new_client.get_api_data()  # pylint: disable=protected-access
@@ -72,3 +96,25 @@ def test_response_to_json(client_setup):  # pylint: disable=redefined-outer-name
 def test_to_dataframe(response_setup):  # pylint: disable=redefined-outer-name
     df = ClientBuilder.api_to_dataframe(response_setup)
     assert isinstance(df, pd.DataFrame)
+
+
+@responses.activate
+def test_get_api_data_with_mocked_response():
+    """Test get_api_data with mocked API response"""
+    endpoint = "https://api.test.com/data"
+    expected_data = {"key": "value", "nested": {"id": 123}}
+
+    # Mock the API response
+    responses.add(
+        responses.GET,
+        endpoint,
+        json=expected_data,
+        status=200
+    )
+
+    client = ClientBuilder(endpoint=endpoint)
+    response = client.get_api_data()
+
+    assert response == expected_data
+    assert len(responses.calls) == 1
+    assert responses.calls[0].request.url == endpoint
diff --git a/tests/test_integration.py b/tests/test_integration.py
new file mode 100644
index 0000000..75128ab
--- /dev/null
+++ b/tests/test_integration.py
@@ -0,0 +1,101 @@
+import pytest
+import responses
+import pandas as pd
+
+from api_to_dataframe import ClientBuilder, RetryStrategies
+
+
+@responses.activate
+def test_full_flow_simple_api():
+    """Test the full flow from API request to DataFrame conversion with a simple API response"""
+    # Setup mock API
+    endpoint = "https://api.example.com/data"
+    # Modificado para retornar lista diretamente, não encapsulado em dicionário
+    api_response = [
+        {"id": 1, "name": "Item 1", "price": 10.99},
+        {"id": 2, "name": "Item 2", "price": 20.50},
+        {"id": 3, "name": "Item 3", "price": 5.25}
+    ]
+
+    responses.add(
+        responses.GET,
+        endpoint,
+        json=api_response,
+        status=200
+    )
+
+    # Create client and fetch data
+    client = ClientBuilder(
+        endpoint=endpoint,
+        retry_strategy=RetryStrategies.LINEAR_RETRY_STRATEGY,
+        retries=3,
+        connection_timeout=5
+    )
+
+    # Get API data
+    response_data = client.get_api_data()
+
+    # Convert to DataFrame
+    df = client.api_to_dataframe(response_data)
+
+    # Assertions
+    assert isinstance(df, pd.DataFrame)
+    assert len(df) == 3
+    assert "id" in df.columns
+    assert "name" in df.columns
+    assert "price" in df.columns
+    assert df.iloc[0]["name"] == "Item 1"
+    assert df.iloc[1]["price"] == 20.50
+    assert df.iloc[2]["id"] == 3
+
+
+@responses.activate
+def test_full_flow_with_retry():
+    """Test the full flow with a failed request that succeeds after retry"""
+    endpoint = "https://api.example.com/data/retry"
+    # Modificado para lista direta, similar ao teste anterior
+    api_response = [
+        {"id": 1, "value": "Success after retry"}
+    ]
+
+    # Add a failing response first
+    responses.add(
+        responses.GET,
+        endpoint,
+        status=500,
+        json={"error": "Server Error"}
+    )
+
+    # Add a successful response for subsequent requests
+    responses.add(
+        responses.GET,
+        endpoint,
+        json=api_response,
+        status=200
+    )
+
+    # Create client with retry strategy
+    client = ClientBuilder(
+        endpoint=endpoint,
+        retry_strategy=RetryStrategies.LINEAR_RETRY_STRATEGY,
+        retries=3,
+        initial_delay=1,
+        connection_timeout=5
+    )
+
+    # Get API data - should succeed after retry
+    response_data = client.get_api_data()
+
+    # Convert to DataFrame
+    df = client.api_to_dataframe(response_data)
+
+    # Assertions
+    assert isinstance(df, pd.DataFrame)
+    assert len(df) == 1
+    assert "id" in df.columns
+    assert "value" in df.columns
+    assert df.iloc[0]["id"] == 1
+    assert df.iloc[0]["value"] == "Success after retry"
+
+    # Verify we had 2 calls (first failed, second succeeded)
+    assert len(responses.calls) == 2
\ No newline at end of file
diff --git a/tests/test_models_get_data.py b/tests/test_models_get_data.py
index 9f80d75..f060277 100644
--- a/tests/test_models_get_data.py
+++ b/tests/test_models_get_data.py
@@ -1,6 +1,8 @@
 import pytest
 import requests
 import responses
+import pandas as pd
+import json
 
 from api_to_dataframe.models.get_data import GetData
 from api_to_dataframe.controller.client_builder import ClientBuilder
@@ -25,6 +27,43 @@ def test_to_emp_dataframe():
         GetData.to_dataframe(response)
 
 
+@responses.activate
+def test_valid_dataframe_conversion():
+    """Test successful conversion of valid data to DataFrame"""
+    # A estrutura do dict afeta como o pandas cria o DataFrame
+    # Os dados precisam estar em uma lista para serem convertidos em linhas
+    valid_data = [{"id": 1, "name": "Test"}, {"id": 2, "name": "Test2"}]
+    df = GetData.to_dataframe(valid_data)
+
+    assert isinstance(df, pd.DataFrame)
+    assert len(df) == 2
+    assert "id" in df.columns
+    assert "name" in df.columns
+    assert df.iloc[0]["id"] == 1
+    assert df.iloc[1]["name"] == "Test2"
+
+
+@responses.activate
+def test_nested_data_conversion():
+    """Test conversion of nested data structures"""
+    # Lista de dicionários é mais adequado para converter em DataFrame
+    nested_data = [
+        {"user": {"id": 1, "profile": {"name": "User1"}}},
+        {"user": {"id": 2, "profile": {"name": "User2"}}}
+    ]
+
+    # Convert to string and back to dict to simulate JSON response
+    json_str = json.dumps(nested_data)
+    response_list = json.loads(json_str)
+
+    df = GetData.to_dataframe(response_list)
+    assert isinstance(df, pd.DataFrame)
+    assert not df.empty
+    assert len(df) == 2
+    # Verificar estrutura das colunas
+    assert "user" in df.columns
+
+
 @responses.activate
 def test_http_error():
     endpoint = "https://api.exemplo.com"
@@ -36,6 +75,23 @@ def test_http_error():
         GetData.get_response(endpoint=endpoint, headers={}, connection_timeout=10)
 
 
+@responses.activate
+def test_http_error_with_custom_message():
+    """Test HTTP error with custom error message in response"""
+    endpoint = "https://api.exemplo.com/error"
+    error_response = {"error": "Bad Request", "message": "Invalid parameters"}
+
+    responses.add(
+        responses.GET,
+        endpoint,
+        json=error_response,
+        status=400
+    )
+
+    with pytest.raises(requests.exceptions.HTTPError):
+        response = GetData.get_response(endpoint=endpoint, headers={}, connection_timeout=10)
+
+
 @responses.activate
 def test_timeout_error():
     endpoint = "https://api.exemplo.com"
@@ -56,3 +112,37 @@ def test_request_exception():
 
     with pytest.raises(requests.exceptions.RequestException):
         GetData.get_response(endpoint=endpoint, headers={}, connection_timeout=10)
+
+
+@responses.activate
+def test_headers_passed_correctly():
+    """Test that headers are correctly passed to the request"""
+    endpoint = "https://api.exemplo.com/headers"
+    expected_response = {"success": True}
+    custom_headers = {
+        "Authorization": "Bearer test-token",
+        "X-Custom-Header": "test-value",
+        "Content-Type": "application/json"
+    }
+
+    def match_headers(request):
+        for key, value in custom_headers.items():
+            if request.headers.get(key) != value:
+                return (400, {}, json.dumps({"error": "Header mismatch"}))
+        return (200, {}, json.dumps(expected_response))
+
+    responses.add_callback(
+        responses.GET,
+        endpoint,
+        callback=match_headers,
+        content_type="application/json"
+    )
+
+    response = GetData.get_response(
+        endpoint=endpoint,
+        headers=custom_headers,
+        connection_timeout=10
+    )
+
+    assert response.status_code == 200
+    assert response.json() == expected_response
diff --git a/tests/test_utils_logger.py b/tests/test_utils_logger.py
new file mode 100644
index 0000000..5f4896e
--- /dev/null
+++ b/tests/test_utils_logger.py
@@ -0,0 +1,23 @@
+import logging
+import pytest
+from api_to_dataframe.utils.logger import logger
+
+
+def test_logger_exists():
+    """Test logger is properly initialized."""
+    assert logger.name == "api-to-dataframe"
+    # Verificar apenas que é uma instância de logger, sem verificar propriedades específicas
+    assert isinstance(logger, logging.Logger)
+
+
+def test_logger_can_log():
+    """Test logger can log messages without errors."""
+    # Tentativa de logging não deve lançar exceções
+    try:
+        logger.info("Test message")
+        logger.warning("Test warning")
+        logger.error("Test error")
+        # Se chegamos aqui, não houve exceções
+        assert True
+    except Exception as e:
+        assert False, f"Logger raised an exception: {e}"
\ No newline at end of file